Python BeautifulSoup解析的问题

我正在尝试用BeautifulSoup解析一个。任务是获取此页面上所有批次的红色下划线数据。我从左侧和右侧区块（关于地块、拍卖名称、国家等）获取数据，但从中央区块获取数据对我来说似乎有问题。下面是所做工作的示例

import requests
import re
from bs4 import BeautifulSoup as bs
import pandas as pd

URL_TEMPLATE = "https://www.artprice.com/artist/15079/wassily-kandinsky/lots/pasts?ipp=100"
FILE_NAME = "test"

def parse(url = URL_TEMPLATE):
    result_list = {'lot': [], 'name': [], 'date': [], 'type1': [], 'type2': [], 'width': [], 'height': [], 'estimate': [], 'hummerprice': [], 'auction_date': [], 'auction': [], 'country': []}
    r = requests.get(URL_TEMPLATE)
    soup = bs(r.text, "html.parser")
    lot_info = soup.find_all('p', class_='hidden-xs')
    date_info = soup.find_all('date')
    names_info = soup.find_all('a', class_='sln_lot_show')
    auction_info = soup.find_all('p', class_='visible-xs')
    auction_date_info = soup.find_all(string=re.compile('\d\d\s\w\w\w\s\d\d\d\d'))[1::2]
    type1_info = soup.find_all('div')
    for i in range(len(lot_info)):
        result_list['lot'].append(lot_info[i].text)
    for i in range(len(date_info)):
        result_list['date'].append(date_info[i].text)
    for i in range (len(names_info)):
        result_list['name'].append(names_info[i].text)
    for i in range(0, len(auction_info), 2):
        result_list['auction'].append(soup.find_all('p', class_='visible-xs')[i].strong.string)
    for i in range(1, len(auction_info), 2):
        result_list['country'].append(soup.find_all('p', class_='visible-xs')[i].string)
    for i in range(len(auction_date_info)):
        result_list['auction_date'].append(auction_date_info[i])
    return result_list
df = pd.DataFrame(data=parse())
df.to_excel("test.xlsx")

---

因此，任务是分别从该页面上每个批次的中心块获取数据。

您需要第n种类型才能访问所有这些

元素

这只是第一个证明它有效的例子。

我让你来清理输出

for div in soup.find_all('div',class_='col-xs-8 col-sm-6'): 
    print(div.select_one('a').text.strip()) 
    print(div.select_one('p:nth-of-type(2)').text.strip()) 
    print(div.select_one('p:nth-of-type(3)').text.strip()) 
    print(div.select_one('p:nth-of-type(4)').text.strip()) 
    break 

结果:

Abstract
Print-Multiple, Print in colors, 29 1/2 x 31 1/2 in75 x 80 cm
Estimate:

              € 560 - € 784


              $ 605 - $ 848


              £ 500 - £ 700


              ￥ 4,303 - ￥ 6,025
Hammer price:
              not communicated
not communicated
not communicated
not communicated

您需要第n种类型才能访问所有这些
元素

这只是第一个证明它有效的例子。

我让你来清理输出

for div in soup.find_all('div',class_='col-xs-8 col-sm-6'): 
    print(div.select_one('a').text.strip()) 
    print(div.select_one('p:nth-of-type(2)').text.strip()) 
    print(div.select_one('p:nth-of-type(3)').text.strip()) 
    print(div.select_one('p:nth-of-type(4)').text.strip()) 
    break 

结果:

Abstract
Print-Multiple, Print in colors, 29 1/2 x 31 1/2 in75 x 80 cm
Estimate:

              € 560 - € 784


              $ 605 - $ 848


              £ 500 - £ 700


              ￥ 4,303 - ￥ 6,025
Hammer price:
              not communicated
not communicated
not communicated
not communicated

看来这就是我一直在寻找的。谢谢！看来这就是我一直在寻找的。谢谢！