Python 如何在 BeautifulSoup 中提取具有相同类名的数据

Question

我正在尝试使用python中的BeautifulSoup库提取数据。我用拉链和汤来提取。

我的 html 数据如下所示：

<li>
<ul class="features">
<li>Year: <strong>2016</strong></li>
<li>Kilometers: <strong>81,000</strong></li>
</ul>
<ul class="features">
<li>Doors: <strong>2 door</strong></li>
<li>Color: <strong>White</strong></li>
</ul>
<ul class="features">
</ul>
</li>

在这里，我想在单独的变量中获取年份，公里，门，颜色。但是当我运行我的代码时，它会聚在一起。

我的代码 ：

for title, price, date, features  in zip(soup.select('.listing-item .title'),
soup.select('.listing-item .price'),
soup.select('.listing-item .date'),
soup.select('.listing-item .features')):

title = title.get_text().strip()
price = price.get_text().strip()
date = date.get_text().strip()
features = features.get_text().strip()
print(features)

输出：

Year: 2016
Kilometers: 81,000
Doors: 2 door
Color: White

如何在单独的变量中存储年份，公里，门，颜色？

Answer 1

你可以试试：

from bs4 import BeautifulSoup as bs
from io import StringIO
data = """<li>
<ul class="features">
<li>Year: <strong>2016</strong></li>
<li>Kilometers: <strong>81,000</strong></li>
</ul>
<ul class="features">
<li>Doors: <strong>2 door</strong></li>
<li>Color: <strong>White</strong></li>
</ul>
<ul class="features">
</ul>
</li>"""
soup = bs(StringIO(data))
Year, Km, Doors, Color = list(map(lambda x: x.text.split(':')[1].strip(), soup.select('.features > li')))
print(Year, Km, Doors, Color)

Answer 2

查找包含文本的元素li，然后查找下一个强标记。 声明空列表并追加。

代码。

from bs4 import BeautifulSoup
html='''<li>
<ul class="features">
<li>Year: <strong>2016</strong></li>
<li>Kilometers: <strong>81,000</strong></li>
</ul>
<ul class="features">
<li>Doors: <strong>2 door</strong></li>
<li>Color: <strong>White</strong></li>
</ul>
<ul class="features">
</ul>
</li>
'''
soup=BeautifulSoup(html,'html.parser')
Year=[]
KiloMeter=[]
Doors=[]
Color=[]
for year,km,dor,colr in zip(soup.select('ul.features li:contains("Year:")'),soup.select('ul.features li:contains("Kilometers:")'),soup.select('ul.features li:contains("Doors:")'),soup.select('ul.features li:contains("Color:")')):
Year.append(year.find_next('strong').text)
KiloMeter.append(km.find_next('strong').text)
Doors.append(dor.find_next('strong').text)
Color.append(colr.find_next('strong').text)
print(Year,KiloMeter,Doors,Color)

输出：列表

['2016'] ['81,000'] ['2 door'] ['White']