python - 如何使用 BeautifulSoup4 从属性中未指定类或 id 的网站中抓取内容

Question

我想将“a”标签中的文本(即只有名称“42mm Architecture”)和“服务范围、已建成项目的类型、已建成项目的位置、工作风格、网站”中的单独内容刮取为 CSV整个网页的文件头及其内容。
元素没有与之关联的类或 ID。所以我有点坚持如何正确提取这些细节，中间还有那些“br”和“b”标签。
在提供的代码块之前和之后有多个“p”标签。这里是 website .

<h2>
  <a href="http://www.dezeen.com/tag/design-by-42mm-architecture" rel="noopener noreferrer" target="_blank">
   42mm Architecture
  </a>
  |
  <span style="color: #808080;">
   Delhi | Top Architecture Firms/ Architects in India
  </span>
 </h2>
 <!-- /wp:paragraph -->
 <p>
  <b>
   Scope of services:
  </b>
  Architecture, Interiors, Urban Design.
  <br/>
  <b>
   Types of Built Projects:
  </b>
  Residential, commercial, hospitality, offices, retail, healthcare, housing, Institutional
  <br/>
  <b>
   Locations of Built Projects:
  </b>
  New Delhi and nearby states
  <b>
   <br/>
  </b>
  <b>
   Style of work
  </b>
  <span style="font-weight: 400;">
   : Contemporary
  </span>
  <br/>
  <b>
   Website
  </b>
  <span style="font-weight: 400;">
   :
   <a href="https://www.42mm.co.in/">
    42mm.co.in
   </a>
  </span>
 </p>

那么它是如何使用 BeautifulSoup4 完成的呢？

Answer 1

这个有点费时间!网页不完整，标签和标识符较少。添加更多内容，他们甚至没有拼写检查内容例如。 一个地方有一个标题Scope of Services另一个地方有Scope of services还有更多这样的!所以我所做的是粗略的提取，如果你也有分页的想法，我相信它会对你有所帮助。

import requests
from bs4 import BeautifulSoup
import csv

page = requests.get('https://www.re-thinkingthefuture.com/top-architects/top-architecture-firms-in-india-part-1/')
soup = BeautifulSoup(page.text, 'lxml')

# there are many h2 tags but we want the one without any class name
h2 = soup.find_all('h2', class_= '')

headers = []
contents = []
header_len = []
a_tags = []

for i in h2:
    if i.find_next().name == 'a':             # to make sure we do not grab the wrong tag
        a_tags.append(i.find_next().text)
        p = i.find_next_sibling()
        contents.append(p.text)
        h =[j.text for j in  p.find_all('strong')]   #  some headings were bold in the website
        headers.append(h)
        header_len.append(len(h))

# since only some headings were in bold the max number of bold would give all headers
headers = headers[header_len.index(max(header_len))]

# removing the : from headings
headers = [i[:len(i)-1] for i in headers]

# inserted a new heading
headers.insert(0, 'Firm')

# n for traversing through headers list
# k for traversing through a_tags list
n =1
k =0

# this is the difficult part where the content will have all the details in one value including the heading like this
"""
Scope of services: Architecture, Interiors, Urban Design.Types of Built Projects: Residential, commercial, hospitality, offices, retail, healthcare, housing, InstitutionalLocations of Built Projects: New Delhi and nearby statesStyle of work: ContemporaryWebsite: 42mm.co.in
"""
# thus I am splitting it using the ':' and then splicing it from the start of the each heading

contents = [i.split(':') for i in contents]
for i in contents:
    for j in i:
        h = headers[n][:5]
        if i.index(j) == 0:
            i[i.index(j)] = a_tags[k]
            n+=1
            k+=1
        elif h in j:
            i[i.index(j)] = j[:j.index(h)]
            j = j[:j.index(h)]
            if n < len(headers)-1:
                n+=1
    n =1

    # merging those extra values in the list if any
    if len(i) == 7:
        i[3] = i[3] + ' ' + i[4]
        i.remove(i[4])

# writing into csv file
# if you don't want a line space between each row then add newline = '' argument in the open function below
with open('output.csv', 'w') as f:   
    writer = csv.writer(f)
    writer.writerow(headers)
    writer.writerows(contents)

这是输出:

如果您想分页，只需将页码添加到网址的末尾即可!

page_num = 1
while page_num <13:
    page = requests.get(f'https://www.re-thinkingthefuture.com/top-architects/top-architecture-firms-in-india-part-1/{page_num}/')

    # paste the above code starting from soup = BeautifulSoup(page.text, 'lxml')

    page_num +=1

希望这会有所帮助，如果有任何错误，请告诉我。
编辑 1:
我忘了说最重要的部分对不起，如果有标签 no class名称，那么您仍然可以使用我在上面的代码中使用的标签来获取标签

h2 = soup.find_all('h2', class_= '')

这只是说给我所有 h2没有类名的标签。这本身有时可以是唯一标识符，因为我们正在使用 no class value来识别它。