python_06

最新推荐文章于 2024-05-30 09:57:45 发布

转载最新推荐文章于 2024-05-30 09:57:45 发布 · 69 阅读

0 ·

CC 4.0 BY-SA版权

原文链接：http://www.cnblogs.com/zhanglei97/p/11049438.html

文章标签：

#python #php

博客介绍了selenium的相关内容，包括剩余用法、万能登录破解、爬取京东商品信息以及破解极验滑动验证码等。还提及了Xpath语法，布置了总结知识点写博客、爬取京东商品信息和滑动验证等作业。

今日内容:
注意: selenium驱动的浏览器是干净的，没有任何缓存。

1、selenium剩余用法
2、selenium万能登录破解
3、selenium爬取京东商品信息
4、破解极验滑动验证码

Xpath语法:

今日作业:
1、总结课堂知识点，写博客
2、爬取京东商品信息
3、滑动验证（提高题）

一、自动登录抽屉新热榜

from selenium import webdriver
import time

driver = webdriver.Chrome(r'D:\BaiduNetdiskDownload\chromedriver_win32\chromedriver.exe')

# 把窗口转成全屏
driver.maximize_window()

try:
    driver.get('https://dig.chouti.com/')
    driver.implicitly_wait(10)
    time.sleep(5)

    # 1、点击登录
    login_btn = driver.find_element_by_id('login_btn')
    login_btn.click()
    time.sleep(2)

    # 2、输入用户名
    phone = driver.find_element_by_class_name('login-phone')
    phone.send_keys('15622792660')

    # 3、输入密码
    pwd = driver.find_element_by_class_name('pwd-password-input')
    pwd.send_keys('kermit46709394')

    # 4、确认登录
    login_submit = driver.find_element_by_class_name('btn-large')
    login_submit.click()

    time.sleep(20)

# 捕获异常并打印
except Exception as e:
    print(e)

finally:
    driver.close()

二、 selenium选择器之Xpath

from selenium import webdriver

driver = webdriver.Chrome(r'D:\BaiduNetdiskDownload\chromedriver_win32\chromedriver.exe')


try:
    # 隐式等待: 写在get请求前
    driver.implicitly_wait(5)

    driver.get('https://doc.scrapy.org/en/latest/_static/selectors-sample1.html')

    # 显式等待: 写在get请求后
    # wait.until(...)

    '''
    
<html>
 <head>
  <base href='http://example.com/' />
  <title>Example website</title>
 </head>
 <body>
  <div id='images'>
   <a href='image1.html'>Name: My image 1 <br /><img src='image1_thumb.jpg' /></a>
   <a href='image2.html'>Name: My image 2 <br /><img src='image2_thumb.jpg' /></a>
   <a href='image3.html'>Name: My image 3 <br /><img src='image3_thumb.jpg' /></a>
   <a href='image4.html'>Name: My image 4 <br /><img src='image4_thumb.jpg' /></a>
   <a href='image5.html'>Name: My image 5 <br /><img src='image5_thumb.jpg' /></a>
  </div>
 </body>
</html>
    '''
    # 根据xpath语法查找元素
    # / 从根节点开始找第一个
    html = driver.find_element_by_xpath('/html')
    # html = driver.find_element_by_xpath('/head')  # 报错
    print(html.tag_name)

    # // 从根节点开始找任意一个节点
    div = driver.find_element_by_xpath('//div')
    print(div.tag_name)

    # @
    # 查找id为images的div节点
    div = driver.find_element_by_xpath('//div[@id="images"]')
    print(div.tag_name)
    print(div.text)

    # 找到第一个a节点
    a = driver.find_element_by_xpath('//a')
    print(a.tag_name)

    # 找到所有a节点
    a_s = driver.find_elements_by_xpath('//a')
    print(a_s)

    # 找到第一个a节点的href属性
    # get_attribute:获取节点中某个属性
    a = driver.find_element_by_xpath('//a').get_attribute('href')
    print(a)

finally:
    driver.close()

三、selenium剩余操作

''''''
'''
点击、清除操作
'''
# from selenium import webdriver
# from selenium.webdriver.common.keys import Keys
# import time
#
# driver = webdriver.Chrome(r'D:\BaiduNetdiskDownload\chromedriver_win32\chromedriver.exe')
#
# try:
#     driver.implicitly_wait(10)
#     # 1、往jd发送请求
#     driver.get('https://www.jd.com/')
#     # 找到输入框输入围城
#     input_tag = driver.find_element_by_id('key')
#     input_tag.send_keys('围城')
#     # 键盘回车
#     input_tag.send_keys(Keys.ENTER)
#     time.sleep(2)
#     # 找到输入框输入墨菲定律
#     input_tag = driver.find_element_by_id('key')
#     input_tag.clear()
#     input_tag.send_keys('墨菲定律')
#     # 找到搜索按钮点击搜索
#     button = driver.find_element_by_class_name('button')
#     button.click()
#     time.sleep(10)
#
# finally:
#     driver.close()


'''
获取cookies  （了解）
'''
# from selenium import webdriver
# import time
#
# driver = webdriver.Chrome(r'D:\BaiduNetdiskDownload\chromedriver_win32\chromedriver.exe')
#
# try:
#     driver.implicitly_wait(10)
#     driver.get('https://www.zhihu.com/explore')
#     print(driver.get_cookies())
#
#     time.sleep(10)
# finally:
#     driver.close()

'''
选项卡
'''
#选项卡管理：切换选项卡，有js的方式windows.open,有windows快捷键：
# ctrl+t等，最通用的就是js的方式
# import time
# from selenium import webdriver
#
# browser = webdriver.Chrome()
# try:
#     browser.get('https://www.baidu.com')
#
#     # execute_script: 执行javascrpit代码
#     # 弹窗操作
#     # browser.execute_script('alert("tank")')
#     # 新建浏览器窗口
#     browser.execute_script(
#         '''
#         window.open();
#         '''
#     )
#     time.sleep(1)
#     print(browser.window_handles)  # 获取所有的选项卡
#     # 切换到第二个窗口
#     # 新:
#     browser.switch_to.window(browser.window_handles[1])
#     # 旧:
#     # browser.switch_to_window(browser.window_handles[1])
#
#     # 第二个窗口往淘宝发送请求
#     browser.get('https://www.taobao.com')
#     time.sleep(5)
#
#     # 切换到第一个窗口
#     browser.switch_to_window(browser.window_handles[0])
#     browser.get('https://www.sina.com.cn')
#
#     time.sleep(10)
# finally:
#     browser.close()


'''
ActionChangs动作链
'''
# from selenium import webdriver
# from selenium.webdriver import ActionChains
# import time
#
# driver = webdriver.Chrome()
# driver.implicitly_wait(10)
# driver.get('http://www.runoob.com/try/try.php?filename=jqueryui-api-droppable')
#
# try:
#
#     # driver.switch_to_frame('iframeResult')
#     # 切换到id为iframeResult的窗口内
#     driver.switch_to.frame('iframeResult')
#
#     # 源位置
#     draggable = driver.find_element_by_id('draggable')
#
#     # 目标位置
#     droppable = driver.find_element_by_id('droppable')
#
#     # 调用ActionChains，必须把驱动对象传进去
#     # 得到一个动作链对象，复制给一个变量
#     actions = ActionChains(driver)
#
#     # 方式一: 机器人
#     # 瞬间把源图片位置秒移到目标图片位置
#     # actions.drag_and_drop(draggable, droppable)  # 编写一个行为
#     # actions.perform()  # 执行编写好的行为
#
#
#     # 方式二: 模拟人的行为
#     source = draggable.location['x']
#     target = droppable.location['x']
#     print(source, target)
#
#     distance = target - source
#     print(distance)
#
#     # perform：每个动作都要调用perform执行
#
#     # 点击并摁住源图片
#     ActionChains(driver).click_and_hold(draggable).perform()
#
#     s = 0
#     while s < distance:
#         # 执行位移操作
#         ActionChains(driver).move_by_offset(xoffset=2, yoffset=0).perform()
#         s += 2
#
#     # 释放动作链
#     ActionChains(driver).release().perform()
#
#     time.sleep(10)
#
#
# finally:
#     driver.close()


'''
前进、后退
'''
# from selenium import webdriver
# import time
#
# driver = webdriver.Chrome()
#
# try:
#     driver.implicitly_wait(10)
#     driver.get('https://www.jd.com/')
#     driver.get('https://www.baidu.com/')
#     driver.get('https://www.cnblogs.com/')
#
#     time.sleep(2)
#
#     # 回退操作
#     driver.back()
#     time.sleep(1)
#     # 前进操作
#     driver.forward()
#     time.sleep(1)
#     driver.back()
#     time.sleep(10)
#
# finally:
#     driver.close()

四、破解登录

from selenium import webdriver
from selenium.webdriver import ChromeOptions
import time
r'''
步骤:
    1、打开文件的查看，显示隐藏文件
    2、找到C:\Users\administortra\AppData\Local\Google\Chrome\User Data
        删除Default文件
    3、重新打开浏览器，并登陆百度账号
        - 此时会创建一个新的Default缓存文件
    4、添加cookies
    5、关闭谷歌浏览器后执行程序
'''
# 获取options对象，参数对象
options = ChromeOptions()

# 获取cookies保存路径
# 'C:\Users\administortra\AppData\Local\Google\Chrome\User Data'
profile_directory = r'--user-data-dir=C:\Users\administortra\AppData\Local\Google\Chrome\User Data'

# 添加用户信息目录
options.add_argument(profile_directory)

# 把参数加载到当前驱动中  chrome_options默认参数，用来接收options对象
driver = webdriver.Chrome(chrome_options=options)

try:
    driver.implicitly_wait(10)
    driver.get('https://www.baidu.com/')
    '''
    BDUSS:*****
    '''
    # 添加用户cookies信息
    # name、value必须小写
    driver.add_cookie({"name": "BDUSS", "value": "用户session字符串"})

    # 刷新操作
    driver.refresh()

    time.sleep(10)

finally:
    driver.close()

五、04 selenium爬取京东商品信息

# ''''''
# '''
# 爬取京东商品信息:
#     请求url:
#         https://www.jd.com/
#     提取商品信息:
#         1.商品详情页
#         2.商品名称
#         3.商品价格
#         4.评价人数
#         5.商品商家
# '''
# from selenium import webdriver
# from selenium.webdriver.common.keys import Keys
# import time
#
# driver = webdriver.Chrome()
#
# try:
#     driver.implicitly_wait(10)
#     # 1、往京东主页发送请求
#     driver.get('https://www.jd.com/')
#
#     # 2、输入商品名称，并回车搜索
#     input_tag = driver.find_element_by_id('key')
#     input_tag.send_keys('macbook')
#     input_tag.send_keys(Keys.ENTER)
#     time.sleep(2)
#
#     # 通过JS控制滚轮滑动获取所有商品信息
#     js_code = '''
#         window.scrollTo(0,5000);
#     '''
#     driver.execute_script(js_code)  # 执行js代码
#
#     # 等待数据加载
#     time.sleep(2)
#
#     # 3、查找所有商品div
#     # good_div = driver.find_element_by_id('J_goodsList')
#     good_list = driver.find_elements_by_class_name('gl-item')
#     n = 1
#     for good in good_list:
#         # 根据属性选择器查找
#         # 商品链接
#         good_url = good.find_element_by_css_selector(
#             '.p-img a').get_attribute('href')
#
#         # 商品名称
#         good_name = good.find_element_by_css_selector(
#             '.p-name em').text.replace("\n", "--")
#
#         # 商品价格
#         good_price = good.find_element_by_class_name(
#             'p-price').text.replace("\n", ":")
#
#         # 评价人数
#         good_commit = good.find_element_by_class_name(
#             'p-commit').text.replace("\n", " ")
#
#         # 商品商家
#         good_from = good.find_element_by_class_name(
#             'J_im_icon').text.replace("\n", " ")
#
#         good_content = f'''
#                     商品链接: {good_url}
#                     商品名称: {good_name}
#                     商品价格: {good_price}
#                     评价人数: {good_commit}
#                     商品商家: {good_from}
#                     \n
#                     '''
#         print(good_content)
#         with open('jd.txt', 'a', encoding='utf-8') as f:
#             f.write(good_content)
#
#     next_tag = driver.find_element_by_link_text('下一页')
#
#     next_tag.click()
#
#     time.sleep(10)
#
#
# finally:
#     driver.close()



''''''
'''
爬取京东商品信息:
    请求url:
        https://www.jd.com/
    提取商品信息:
        1.商品详情页
        2.商品名称
        3.商品价格
        4.评价人数
        5.商品商家
'''
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import time


def get_good(driver):
    try:

        # 通过JS控制滚轮滑动获取所有商品信息
        js_code = '''
            window.scrollTo(0,5000);
        '''
        driver.execute_script(js_code)  # 执行js代码

        # 等待数据加载
        time.sleep(2)

        # 3、查找所有商品div
        # good_div = driver.find_element_by_id('J_goodsList')
        good_list = driver.find_elements_by_class_name('gl-item')
        n = 1
        for good in good_list:
            # 根据属性选择器查找
            # 商品链接
            good_url = good.find_element_by_css_selector(
                '.p-img a').get_attribute('href')

            # 商品名称
            good_name = good.find_element_by_css_selector(
                '.p-name em').text.replace("\n", "--")

            # 商品价格
            good_price = good.find_element_by_class_name(
                'p-price').text.replace("\n", ":")

            # 评价人数
            good_commit = good.find_element_by_class_name(
                'p-commit').text.replace("\n", " ")

            good_content = f'''
                        商品链接: {good_url}
                        商品名称: {good_name}
                        商品价格: {good_price}
                        评价人数: {good_commit}
                        \n
                        '''
            print(good_content)
            with open('jd.txt', 'a', encoding='utf-8') as f:
                f.write(good_content)

        next_tag = driver.find_element_by_class_name('pn-next')
        next_tag.click()

        time.sleep(2)

        # 递归调用函数
        get_good(driver)

        time.sleep(10)

    finally:
        driver.close()


if __name__ == '__main__':

    good_name = input('请输入爬取商品信息:').strip()

    driver = webdriver.Chrome()
    driver.implicitly_wait(10)
    # 1、往京东主页发送请求
    driver.get('https://www.jd.com/')

    # 2、输入商品名称，并回车搜索
    input_tag = driver.find_element_by_id('key')
    input_tag.send_keys(good_name)
    input_tag.send_keys(Keys.ENTER)
    time.sleep(2)

    get_good(driver)

作业：破解极限滑动验证

''''''
'''
破解极验滑动验证
博客园登录url:
    https://account.cnblogs.com/signin?returnUrl=https%3A%2F%2Fwww.cnblogs.com%2F
1、输入用户名与密码，并点击登录
2、弹出滑动验证，获取有缺口与完整的图片
3、通过像素点进行比对，获取滑动位移距离
4、模拟人的行为轨迹
5、开始滑动
'''
from selenium import webdriver  # 用来驱动浏览器的
from selenium.webdriver import ActionChains  # 破解滑动验证码的时候用的 可以拖动图片
import time
from PIL import Image  # pip3 install pillow
import random

option = webdriver.ChromeOptions()
option.add_argument('disable-infobars')

driver = webdriver.Chrome(chrome_options=option)


def get_snap(driver):
    # selenium自带的截图网页全屏图片
    driver.save_screenshot('snap.png')

    img = driver.find_element_by_class_name('geetest_canvas_img')

    left = img.location['x']

    upper = img.location['y']

    right = left + img.size['width']
    lower = upper + img.size['height']

    # print(left, upper, right, lower)
    img_obj = Image.open('snap.png')

    # 对屏幕进行截取,获取滑动验证图片
    image = img_obj.crop((left, upper, right, lower))

    return image


def get_image1(driver):
    time.sleep(0.2)
    js_code = '''
    var x = document.getElementsByClassName('geetest_canvas_fullbg')[0].style.display="block";
    console.log(x)
    '''

    time.sleep(1)
    driver.execute_script(js_code)

    # 截取图片
    img_obj = get_snap(driver)

    return img_obj


def get_image2(driver):
    time.sleep(0.2)

    js_code = '''
    var x = document.getElementsByClassName('geetest_canvas_fullbg')[0].style.display="none";
    console.log(x)
    '''

    driver.execute_script(js_code)

    time.sleep(1)

    # 截取图片
    img_obj = get_snap(driver)

    return img_obj


def get_distance(image1, image2):
    # 初始值
    start = 60

    # 滑块色差
    color_num = 60

    for x in range(start, image1.size[0]):
        for y in range(image1.size[1]):

            rgb1 = image1.load()[x, y]

            rgb2 = image2.load()[x, y]

            r = abs(rgb1[0] - rgb2[0])
            g = abs(rgb1[1] - rgb2[1])
            b = abs(rgb1[2] - rgb2[2])

            if not (r < color_num and g < color_num and b < color_num):
                return x - 7


def get_stacks(distance):
    distance += 20

    '''
    匀加速\减速运行
        v = v0 + a * t

    位移:
    s = v * t + 0.5 * a * (t**2)
    '''

    # 初速度
    v0 = 0

    # 加减速度列表
    a_list = [3, 4, 5]

    # 时间
    t = 0.2

    # 初始位置
    s = 0

    # 向前滑动轨迹
    forward_stacks = []

    mid = distance * 3 / 5

    while s < distance:
        if s < mid:
            a = a_list[random.randint(0, 2)]

        else:
            a = -a_list[random.randint(0, 2)]

        v = v0

        stack = v * t + 0.5 * a * (t ** 2)

        # 每次拿到的位移
        stack = round(stack)

        s += stack

        v0 = v + a * t

        forward_stacks.append(stack)

    back_stacks = [-1, -1, -2, -3, -2, -3, -2, -2, -3, -1]

    return {'forward_stacks': forward_stacks, 'back_stacks': back_stacks}


def main():
    try:

        driver.get('https://passport.cnblogs.com/user/signin')
        driver.implicitly_wait(5)

        # 1.输入用户名与密码,点击登录
        username = driver.find_element_by_id('LoginName')
        password = driver.find_element_by_id('Password')
        login_button = driver.find_element_by_class_name('ladda-label')
        time.sleep(1)
        username.send_keys('_tank_')
        time.sleep(1)
        password.send_keys('k46709394.')

        # 这里需要等待账号密码输入完毕后再点击登录按钮，否则的不弹框
        time.sleep(1)
        login_button.click()
        # time.sleep(3)

        # 2.点击滑动验证按钮,获取图片
        geetest_button = driver.find_element_by_class_name('geetest_slider_button')
        geetest_button.click()

        time.sleep(0.2)

        # 3.针对完整的图片进行截取
        image1 = get_image1(driver)

        # 4.针对有缺口的图片进行截取
        image2 = get_image2(driver)

        # 5.对比两张图片,获取滑动距离
        distance = get_distance(image1, image2)

        # 6.模拟人为滑动轨迹
        stacks = get_stacks(distance)

        # 7.根据滑动轨迹进行滑动
        forward_stacks = stacks['forward_stacks']
        back_stacks = stacks['back_stacks']

        slider_button = driver.find_element_by_class_name('geetest_slider_button')
        time.sleep(0.2)

        ActionChains(driver).click_and_hold(slider_button).perform()

        time.sleep(0.2)
        for forward_stack in forward_stacks:
            ActionChains(driver).move_by_offset(xoffset=forward_stack, yoffset=0).perform()
            time.sleep(0.1)
        for back_stack in back_stacks:
            ActionChains(driver).move_by_offset(xoffset=back_stack, yoffset=0).perform()
            time.sleep(0.1)

        time.sleep(0.2)

        ActionChains(driver).move_by_offset(xoffset=5, yoffset=0).perform()
        ActionChains(driver).move_by_offset(xoffset=-5, yoffset=0).perform()

        ActionChains(driver).release().perform()

        time.sleep(50)


    finally:
        driver.close()


if __name__ == '__main__':
    main()