数据之路 - Python爬虫 - PyQuery库

短命女 2023-06-02 11:52 17阅读 0赞

# 一、什么是PyQuery？ #

PyQuery库也是一个非常强大又灵活的网页解析库。

官网地址：[http://pyquery.readthedocs.io/en/latest/][http_pyquery.readthedocs.io_en_latest]

#  二、PyQuery基本库使用 #

html = '''
    <div> 
    　　<ul> 
    　　　　<li class="item-0">first item<lli> 
    　　　　<li class="item-1"><a href="link2.html"＞second item</a><lli> 
    　　　　<li class="item-0 active"><a href="link3.html"><span class="bold"＞third item</span></a></li> 
    　　　　<li class ="item-1 active"><a href="link4 . html">fourth item</a></li> 
    　　　　<li class="item-0"＞＜a href="link5.html">fifth item</a></li> 
    　　</ul> 
    </div>
    '''

## 1.初始化 ##

# 字符串初始化
    from pyquery import PyQuery as pq
    html = ""
    doc = pd(html)
    print(doc('li'))
    
    # URL初始化
    from pyquery import PyQuery as pq
    html = ""
    doc = pq(url=' https://cuiqingcai.com’) 
    print(doc(’title'))
    
    # 文件初始化
    from  pyquery import  PyQuery as pq
    html = ""
    doc = pq(filename=’demo.html’) 
    print(doc(’li’))

## 2.CSS选择器-获取标签 ##

from pyquery import PyQuery as pq
    doc = pd(html)
    
    # 子元素
    items = doc('.list')
    lis = items.find('li')
    
    lis = items.children()
    lis = items.children('.active')
    print(lis)
    
    # 父元素
    items = doc('.list')
    container =items.parents()
    print(container)
    
    parent = items.parents('.wrap')
    print(parent)
    
    # 兄弟元素
    li = doc('.list.item-0.active')
    print(li.siblings())
    print(li.siblings('.active'))

## 3.CSS选择器-获取属性 ##

from pyquery import PyQuery as pq
    doc = pd(html)
    a = doc('.item-0.active a')
    print(a)
    print(a.attr.href)
    print(a.attr('href')

## 4.获取内容 ##

from pyquery import PyQuery as pq
    doc = pd(html)
    a = doc('.item-0.active a')
    print(a)
    print(a.text())

## 5.获取HTML ##

from pyquery import PyQuery as pq
    doc = pd(html)
    li = doc('.item-0.active')
    print(li)
    print(li.html())

转载于:https://www.cnblogs.com/Iceredtea/p/11294266.html

[http_pyquery.readthedocs.io_en_latest]: http://pyquery.readthedocs.io/en/latest/