<h3>
<a href="article.jsp?tp=&arnumber=16">
Granular computing based
<span class="snippet">data</span>
<span class="snippet">mining</span>
in the views of rough set and fuzzy set
</a>
</h3>
使用Python我想从锚标签中获取值,这应该是基于粗糙集和模糊集视图中的粒度计算的数据挖掘
我尝试使用 lxml
parser = etree.HTMLParser()
tree = etree.parse(StringIO.StringIO(html), parser)
xpath1 = "//h3/a/child::text() | //h3/a/span/child::text()"
rawResponse = tree.xpath(xpath1)
print rawResponse
并得到以下输出
['\r\n\t\t','\r\n\t\t\t\t\t\t\t\t\tgranular computing based','data','mining','in the view of roughset and fuzzyset\r\n\t\t\t\t\t\t\]
您可以使用
text_content
方法:
import lxml.html as LH
html = '''<h3>
<a href="article.jsp?tp=&arnumber=16">
Granular computing based
<span class="snippet">data</span>
<span class="snippet">mining</span>
in the views of rough set and fuzzy set
</a>
</h3>'''
root = LH.fromstring(html)
for elt in root.xpath('//a'):
print(elt.text_content())
产量
Granular computing based
data
mining
in the views of rough set and fuzzy set
或者,要删除空格,您可以使用
print(' '.join(elt.text_content().split()))
获得
Granular computing based data mining in the views of rough set and fuzzy set
这是您可能会发现有用的另一个选项:
print(' '.join([elt.strip() for elt in root.xpath('//a/descendant-or-self::text()')]))
产量
Granular computing based data mining in the views of rough set and fuzzy set
(请注意,它在
data
和 mining
之间留下了额外的空格。)
'//a/descendant-or-self::text()'
是更通用的版本
"//a/child::text() | //a/span/child::text()"
。它将遍历所有子代和孙代等。