如何从没有 class 或在 BeautifulSoup4 属性中指定 id 的网站抓取内容
How to scrape content from a website with no class or id specified in attribute with BeautifulSoup4
我想抓取单独的内容,比如 'a' 标签中的文本(即只有名称 - “42mm Architecture”)和 'scope of services, types of built projects, Locations of Built Projects, Style of work, Website' 作为 CSV 文件 headers 及其内容对于整个网页。
这些元素没有 Class 或与之关联的 ID。所以我对如何正确提取这些细节有些困惑,中间还有 'br' 和 'b' 标签。
提供的代码块前后有多个 'p' 标记。这是 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>
那么使用 BeautifulSoup4 是如何完成的呢?
这个有点费时间!该网页不完整,标签和标识符较少。更重要的是,他们甚至没有对内容进行拼写检查 Eg. 一个地方的标题是 Scope of Services
,另一个地方的标题是 Scope of services
,还有更多像那样!所以我所做的是粗略提取,如果您也有分页的想法,我相信它会对您有所帮助。
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 url 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
希望对您有所帮助,如果有任何错误,请告诉我。
编辑 1:
我忘了说最重要的部分抱歉,如果有一个带有 no class
名称的标签,那么您仍然可以使用我在上面的代码中使用的标签
h2 = soup.find_all('h2', class_= '')
这只是说给我所有没有 class 名称的 h2
标签。这本身有时可以是一个唯一的标识符,因为我们使用这个 no class value
来识别它。
您可以使用此示例作为基础如何从该页面抓取信息:
import requests
import pandas as pd
url = "https://www.gov.uk/government/publications/endorsing-bodies-start-up/start-up"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
parent = soup.select_one("div.govspeak")
mapping = {"sector": "sectors", "endorses businesses": "endorses businesses in"}
all_data = []
for h3 in parent.select("h3"):
name = h3.text
link = h3.a["href"] if h3.a else "-"
ul = h3.find_next("ul")
if ul and ul.find_previous("h3") == h3 and ul.parent == parent:
li = [
list(map(lambda x: mapping.get((i := x.strip()), i), v))
for li in ul.select("li")
if len(v := li.get_text(strip=True).split(":")) == 2
]
else:
li = []
all_data.append({"name": name, "link": link, **dict(li)})
df = pd.DataFrame(all_data)
print(df)
df.to_csv("data.csv", index=False)
创建 data.csv
(来自 LibreOffice 的屏幕截图):
我想抓取单独的内容,比如 'a' 标签中的文本(即只有名称 - “42mm Architecture”)和 'scope of services, types of built projects, Locations of Built Projects, Style of work, Website' 作为 CSV 文件 headers 及其内容对于整个网页。
这些元素没有 Class 或与之关联的 ID。所以我对如何正确提取这些细节有些困惑,中间还有 'br' 和 'b' 标签。
提供的代码块前后有多个 'p' 标记。这是 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>
那么使用 BeautifulSoup4 是如何完成的呢?
这个有点费时间!该网页不完整,标签和标识符较少。更重要的是,他们甚至没有对内容进行拼写检查 Eg. 一个地方的标题是 Scope of Services
,另一个地方的标题是 Scope of services
,还有更多像那样!所以我所做的是粗略提取,如果您也有分页的想法,我相信它会对您有所帮助。
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 url 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
希望对您有所帮助,如果有任何错误,请告诉我。
编辑 1:
我忘了说最重要的部分抱歉,如果有一个带有 no class
名称的标签,那么您仍然可以使用我在上面的代码中使用的标签
h2 = soup.find_all('h2', class_= '')
这只是说给我所有没有 class 名称的 h2
标签。这本身有时可以是一个唯一的标识符,因为我们使用这个 no class value
来识别它。
您可以使用此示例作为基础如何从该页面抓取信息:
import requests
import pandas as pd
url = "https://www.gov.uk/government/publications/endorsing-bodies-start-up/start-up"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
parent = soup.select_one("div.govspeak")
mapping = {"sector": "sectors", "endorses businesses": "endorses businesses in"}
all_data = []
for h3 in parent.select("h3"):
name = h3.text
link = h3.a["href"] if h3.a else "-"
ul = h3.find_next("ul")
if ul and ul.find_previous("h3") == h3 and ul.parent == parent:
li = [
list(map(lambda x: mapping.get((i := x.strip()), i), v))
for li in ul.select("li")
if len(v := li.get_text(strip=True).split(":")) == 2
]
else:
li = []
all_data.append({"name": name, "link": link, **dict(li)})
df = pd.DataFrame(all_data)
print(df)
df.to_csv("data.csv", index=False)
创建 data.csv
(来自 LibreOffice 的屏幕截图):