获取某招聘网token

import random

import requests
from selenium import webdriver #获得浏览器驱动
import time
import cv2
import numpy as np
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By

#获得谷歌浏览器驱动，注意一定要大写浏览器名称
driver=webdriver.Chrome(executable_path="C:/Users/chromedriver.exe")
#输入要打开的网址
url="https://www.liepin.com/"
driver.get(url)
time.sleep(4)
driver.find_element(By.XPATH, '//*[@id="home-banner-login-container"]/div/div/div/div/div[2]/div/div[2]').click()
driver.find_element(By.ID, 'login').send_keys("")
driver.find_element(By.ID, 'pwd').send_keys("密码")
driver.find_element(By.XPATH, '//*[@id="home-banner-login-container"]/div/div/div/div/div[4]/div/label/span[2]/span').click()
driver.find_element(By.XPATH, '//*[@id="home-banner-login-container"]/div/div/div/div/div[3]/div/form/button').click()

# #太快看不到添加sleep


while True:
    time.sleep(random.randint(5,10))
    # 获取两张图片,没办法获取到标签元素
    driver.get(url)
    time.sleep(random.randint(2,5))
    url_s = driver.find_element(By.XPATH, '//*[@id="slideBg"]/@src')
    url_b = driver.find_element(By.XPATH, '//*[@id="slideBlock"]/@src')
    print(url_s)
    print("==>"*20)
    print(url_b)
    break
    headers = {
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) 
AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.41 Safari/537.36'
    }
    res_s = requests.get(url_s, headers=headers)
    data_s = res_s.content
    res_b = requests.get(url_b, headers=headers)
    data_b = res_b.content
    # 保存图片
    with open('pic_s.png', 'wb')as f:
        f.write(data_s)
    with open('pic_b.png', 'wb')as f:
        f.write(data_b)

    # 使用opencv读取两张图片
    simg = cv2.imread('pic_s.png')
    bimg = cv2.imread('pic_b.png')

    # 灰度处理，降低偏差
    s_img = cv2.cvtColor(simg, cv2.COLOR_BGR2GRAY)
    b_img = cv2.cvtColor(bimg, cv2.COLOR_BGR2GRAY)

    # 保存两张灰度处理的图片
    cv2.imwrite('hui_simg.png', s_img)
    cv2.imwrite('hui_bimg.png', b_img)

    # 处理滑块图片，保存有效部分
    s_img = s_img[s_img.any(1)]

    # opencv的匹配算法，匹配模块寻找两张图片的相似之处
    result = cv2.matchTemplate(b_img, s_img, cv2.TM_CCOEFF_NORMED)
    print('result', result)

    # 获取坐标
    # 获取最大索引
    index_max = np.argmax(result)
    # 获取到坐标
    y, x = np.unravel_index(index_max, result.shape)
    print("y:", y, "x:", x)

    # 定位到滑块
    ele = driver.find_element_by_xpath('//*[@id="tcaptcha_drag_thumb"]')

    # 实例化对象
    action = ActionChains(driver)
    # 拖动滑块
    time.sleep(1)
    action.drag_and_drop_by_offset(ele, xoffset=x, yoffset=0).perform()
    text = driver.find_element_by_xpath('//*[@id="tcaptcha_note"]').text
    import re
    if re.search('这题|请',text):
        print("no success")
        time.sleep(random.randint(1, 5))
    if text == "验证成功":
        print("成功了")
        time.sleep(60)
        break
driver.quit()