爬取58同城二手电脑一页的商品数据，requests+BeautifulSoup

爬取58同城二手电脑一页的商品数据（35个商品），不要网站推广的商品，只爬取普通个人的商品；每个商品爬取的数据有：'标题'、价格'、'分类'、'区域'、'浏览量'（浏览量没能正确获取，用selenium能获取浏览量，在此没有具体描述）
58同城平板电脑页：https://bj.58.com/pbdn/0/
详情页：
https://bj.58.com/pingbandiannao/41525432516648x.shtml?link_abtest=&psid=195682258207684760008335092&entinfo=41525432516648_p&slot=-1&iuType=p_1&PGTID=0d305a36-0000-1ad2-2601-c5a3525b5373&ClickID=1

元素中有子孙级元素的多段文字，用stripped_strings处理,即：list(soup.select('div.nav')[0].stripped_strings)

import requests
from bs4 import BeautifulSoup
import time

# 给定商品概览页，爬取数据，返回多个电脑详情的url，列表形式
def get_computer_urls(url):
    computer_urls = []
    raw_page = requests.get(url).text
    print('正在打开网页：',url)
    time.sleep(3)
    soup = BeautifulSoup(raw_page,'lxml')
    eles = soup.select('tr[infotag*=commoninfo]>td>a')   # 普通个人的商品，不是网站推广的商品
    print('正在定位元素，选择器是：','tr[infotag*=commoninfo]>td>a')
    for e in eles:
        url = e.get('href')
        computer_urls.append(url)
    return computer_urls

# 给定电脑详情页，返回电脑信息，字典格式
def get_computer_info(url):
    raw_page = requests.get(url).text
    print('正在打开网页：', url)
    time.sleep(3)
    soup = BeautifulSoup(raw_page,'lxml')

    title = soup.select('h1.detail-title__name')[0].get_text().strip()
    category = list(soup.select('div.nav')[0].stripped_strings)
    category = ''.join(category)
    price = soup.select('span.infocard__container__item__main__text--price')[0].get_text().strip()
    address = list(soup.select('div.infocard__container__item__main')[1].stripped_strings)
    address = ''.join(address)
    look_num = soup.select('span#totalcount')[0].get_text().strip()
    #print({'标题':title,'价格':price,'分类':category,'区域':address,'浏览量':look_num})
    return {'标题':title,'价格':price,'分类':category,'区域':address,'浏览量':look_num}


start_url = 'https://bj.58.com/pbdn/0/'
computer_urls = get_computer_urls(start_url)
print(computer_urls)
print('len(computer_urls):',len(computer_urls))
time.sleep(3)
i = 0
for url in computer_urls:
    i +=1
    dict = get_computer_info(url)
    print(i, dict)