用基于python的appium爬取b站直播消费记录

from appium import webdriver
import numpy as np
import pandas as pd
import time

desired_caps = {
    'platformName': 'Android',  # 被测手机是安卓
    'platformVersion': '10',  # 手机安卓版本
    'deviceName': 'xxx',  # 设备名，安卓手机可以随意填写
    'appPackage': 'tv.danmaku.bili',  # 启动APP Package名称
    'appActivity': '.ui.splash.SplashActivity',  # 启动Activity名称
    'unicodeKeyboard': True,  # 使用自带输入法，输入中文时填True
    'resetKeyboard': True,  # 执行完程序恢复原来输入法
    'noReset': True,  # 不要重置App，如果为False的话，执行完脚本后，app的数据会清空，比如你原本登录了，执行完脚本后就退出登录了
    'newCommandTimeout': 6000,
    'automationName': 'UiAutomator2'
}

# 连接Appium Server，初始化自动化环境
driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)
# 设置等待时间，如果不给时间的话可能会找不到元素
driver.implicitly_wait(4)

flick_start_x=540
flick_start_y=192
flick_distance=1050
while True:
    driver.swipe(flick_start_x,flick_start_y+flick_distance,flick_start_x,flick_start_y)

pay_name_list=[]
present_price_list=[]
pay_room_list=[]
pay_ru_name_list=[]
pay_time_list=[]
flick_start_x=540
flick_start_y=192
flick_distance=1050
while True:
    pay_name=driver.find_elements_by_id('pay_name')
    for i in range(len(pay_name)):
        pay_name_list.append(pay_name[i].text)
    present_price=driver.find_elements_by_id('present_price')
    for i in range(len(present_price)):
        present_price_list.append(present_price[i].text)
    pay_room=driver.find_elements_by_id('pay_room')
    for i in range(len(pay_room)):
        pay_room_list.append(pay_room[i].text)
    pay_ru_name=driver.find_elements_by_id('pay_ru_name')
    for i in range(len(pay_ru_name)):
        pay_ru_name_list.append(pay_ru_name[i].text)
    pay_time=driver.find_elements_by_id('pay_time')
    for i in range(len(pay_time)):
        pay_time_list.append(pay_time[i].text)
    driver.swipe(flick_start_x,flick_start_y+flick_distance,flick_start_x,flick_start_y)
    time.sleep(2)

a=pd.DataFrame([pay_name_list,present_price_list,pay_room_list,pay_ru_name_list,pay_time_list],index=['pay_name_list','present_price_list','pay_room_list','pay_ru_name_list','pay_time_list'])
pd.DataFrame(a.T).head(50)