我有一个网址，比如 http://www.bbc.com/news/world/asia/。就在这个页面中，我想提取所有包含 India 或 INDIA 或 india 的链接(应该不区分大小写)。
如果我单击任何输出链接，它应该将我带到相应的页面，例如，这些是印度 印度对 Dhoni 退役感到震惊 和 印度雾继续造成的几行困惑。如果我点击这些链接，我应该被重定向到 http://www.bbc.com/news/world-asia-india-30640436 和 http://www.bbc.com/分别为 news/world-asia-india-30630274。
import urllib
from bs4 import BeautifulSoup
import re
import requests
url = "http://www.bbc.com/news/world/asia/"
r = requests.get(url)
data = r.text
soup = BeautifulSoup(data)
only_links = SoupStrainer('a', href=re.compile('india'))
print (only_links)
我在 python 3.4.2 中编写了非常基本的最小代码。
最佳答案
您需要搜索单词 india在显示的文本中。为此，您需要一个自定义函数:
from bs4 import BeautifulSoup
import requests
url = "http://www.bbc.com/news/world/asia/"
r = requests.get(url)
soup = BeautifulSoup(r.content)
india_links = lambda tag: (getattr(tag, 'name', None) == 'a' and
'href' in tag.attrs and
'india' in tag.get_text().lower())
results = soup.find_all(india_links)
india_links lambda 找到所有 <a> 的标签与 href 的链接属性并包含 india (不区分大小写)显示文本中的某处。
请注意，我使用了 requests响应对象 .content 属性；解码交给 BeautifulSoup!
演示:
>>> from bs4 import BeautifulSoup
>>> import requests
>>> url = "http://www.bbc.com/news/world/asia/"
>>> r = requests.get(url)
>>> soup = BeautifulSoup(r.content)
>>> india_links = lambda tag: getattr(tag, 'name', None) == 'a' and 'href' in tag.attrs and 'india' in tag.get_text().lower()
>>> results = soup.find_all(india_links)
>>> from pprint import pprint
>>> pprint(results)
[<a href="/news/world/asia/india/">India</a>,
<a class="story" href="/news/world-asia-india-30647504" rel="published-1420102077277">India scheme to monitor toilet use </a>,
<a class="story" href="/news/world-asia-india-30640444" rel="published-1420022868334">India to scrap tax breaks on cars</a>,
<a class="story" href="/news/world-asia-india-30640436" rel="published-1420012598505">India shock over Dhoni retirement</a>,
<a href="/news/world/asia/india/">India</a>,
<a class="headline-anchor" href="/news/world-asia-india-30630274" rel="published-1419931669523"><img alt="A Delhi police officer with red flag walks amidst morning fog in Delhi, India, Monday, Dec 29, 2014. " src="http://news.bbcimg.co.uk/media/images/79979000/jpg/_79979280_79979240.jpg"/><span class="headline heading-13">India fog continues to cause chaos</span></a>,
<a class="headline-anchor" href="/news/world-asia-india-30632852" rel="published-1419940599384"><span class="headline heading-13">Court boost to India BJP chief</span></a>,
<a class="headline-anchor" href="/sport/0/cricket/30632182" rel="published-1419930930045"><span class="headline heading-13">India captain Dhoni quits Tests</span></a>,
<a class="story" href="http://www.bbc.co.uk/news/world-radio-and-tv-15386555" rel="published-1392018507550"><img alt="A woman riding a scooter waits for a traffic signal along a street in Mumbai February 5, 2014." src="http://news.bbcimg.co.uk/media/images/72866000/jpg/_72866856_020889093.jpg"/>Special report: India Direct</a>,
<a href="/2/hi/south_asia/country_profiles/1154019.stm">India</a>]
注意 http://www.bbc.co.uk/news/world-radio-and-tv-15386555链接在这里；我们不得不使用 lambda搜索因为使用 text 进行搜索正则表达式不会找到该元素；包含的文本(特别报告:India Direct)不是标签中的唯一元素，因此不会被找到。
类似的问题适用于 /news/world-asia-india-30632852关联;嵌套 <span>元素使得 Court boost to India BJP chief 标题文本不是链接标签的直接子元素。
您可以提取只是链接:
from urllib.parse import urljoin
result_links = [urljoin(url, tag['href']) for tag in results]
所有相对 URL 都相对于原始 URL 进行解析:
>>> from urllib.parse import urljoin
>>> result_links = [urljoin(url, tag['href']) for tag in results]
>>> pprint(result_links)
['http://www.bbc.com/news/world/asia/india/',
'http://www.bbc.com/news/world-asia-india-30647504',
'http://www.bbc.com/news/world-asia-india-30640444',
'http://www.bbc.com/news/world-asia-india-30640436',
'http://www.bbc.com/news/world/asia/india/',
'http://www.bbc.com/news/world-asia-india-30630274',
'http://www.bbc.com/news/world-asia-india-30632852',
'http://www.bbc.com/sport/0/cricket/30632182',
'http://www.bbc.co.uk/news/world-radio-and-tv-15386555',
'http://www.bbc.com/2/hi/south_asia/country_profiles/1154019.stm']
关于python - 如何使用python从网站中提取带有匹配词的html链接，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/27730041/