python爬蟲數據解析的四種不一樣選擇器Xpath，Beautiful Soup，pyquery，re

時間 2020-05-06

標籤 python 爬蟲數據解析四種不一樣選擇器 xpath beautiful soup pyquery 欄目 Python 简体版

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這裏主要是作一個關於數據爬取之後的數據解析功能的整合，方便查閱，以防混淆html

主要講到的技術有Xpath，BeautifulSoup，PyQuery，re（正則）spa

首先舉出兩個做示例的代碼，方便後面舉例code

解析以前須要先將html代碼轉換成相應的對象，各自的方法以下：orm

Xpath：xml

In [7]: from lxml import etree In [8]: text = etree.HTML(html)

BeautifulSoup：htm

In [2]: from bs4 import BeautifulSoup In [3]: soup = BeautifulSoup(html, 'lxml')

PyQuery：對象

In [10]: from pyquery import PyQuery as pq In [11]: doc = pq(html)

re：沒有須要的對象，他是直接對字符串進行匹配的規則blog

示例1three

html = ''' <html><head><title>The Dormouse's story</title></head>
<body>
<p class="title"><b>The Dormouse's story</b></p>

<p class="story">Once upon a time there were three little sisters; and their names were <a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>, <a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and <a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>; and they lived at the bottom of a well.</p>

<p class="story">...</p>
</body>
</html> '''

接下來咱們來用不一樣的解析方法分析示例的HTML代碼ip

匹配標題內容：

Xpath：

In [16]: text.xpath('//title/text()')[0] Out[16]: "The Dormouse's story"

BeautifulSoup：

In [18]: soup.title.string Out[18]: "The Dormouse's story"

PyQuery：

In [20]: doc('title').text() Out[20]: "The Dormouse's story"

re:

In [11]: re.findall(r'<title>(.*?)</title></head>', html)[0] Out[11]: "The Dormouse's story"

匹配第三個a標籤的href屬性：

Xpath：#推薦

In [36]: text.xpath('//a[@id="link3"]/@href')[0] Out[36]: 'http://example.com/tillie'

BeautifulSoup：

In [27]: soup.find_all(attrs={'id':'link3'})
Out[27]: [<a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]


In [33]: soup.find_all(attrs={'id':'link3'})[0].attrs['href']
Out[33]: 'http://example.com/tillie'

PyQuery：#推薦

In [45]: doc("#link3").attr.href Out[45]: 'http://example.com/tillie'

re:

In [46]: re.findall(r'<a href="(.*?)" class="sister" id="link3">Tillie</a>;', html)[0] Out[46]: 'http://example.com/tillie'

匹配P標籤即是內容的所有數據：

Xpath：

In [48]: text.xpath('string(//p[@class="story"])').strip() Out[48]: 'Once upon a time there were three little sisters; and their names were\nElsie,\nLacie and\nTillie;\nand they lived at the bottom of a well.' In [51]: ' '.join(text.xpath('string(//p[@class="story"])').split('\n')) Out[51]: 'Once upon a time there were three little sisters; and their names were Elsie, Lacie and Tillie; and they lived at the bottom of a well.'

BeautifulSoup：

In [89]: ' '.join(list(soup.body.stripped_strings)).replace('\n', '') Out[89]: "The Dormouse's story Once upon a time there were three little sisters; and their names were Elsie,Lacie and Tillie; and they lived at the bottom of a well. ..."

PyQuery:

In [99]: doc('.story').text() Out[99]: 'Once upon a time there were three little sisters; and their names were Elsie, Lacie and Tillie; and they lived at the bottom of a well. ...'

re：不推薦使用，過於麻煩

In [101]: re.findall(r'<p class="story">(.*?)<a href="http://example.com/elsie" class="sister" id="link1">(.*?)</a>(.*?)<a href="http://example.com/lacie" class="siste
     ...: r" id="link2">(.*?)</a>(.*?)<a href="http://example.com/tillie" class="sister" id="link3">(.*?)</a>;(.*?)</p>', html, re.S)[0]
Out[101]: ('Once upon a time there were three little sisters; and their names were\n', 'Elsie', ',\n', 'Lacie', ' and\n', 'Tillie', '\nand they lived at the bottom of a well.')

示例2

html = ''' <div>
<ul>
<li class="item-0">first item</li>
<li class="item-1"><a href="link2.html">second item</a></li>
<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> '''

匹配second item

Xpath：

In [14]: text.xpath('//li[2]/a/text()')[0] Out[14]: 'second item'

BeautifulSoup：

In [23]: soup.find_all(attrs={'class': 'item-1'})[0].string Out[23]: 'second item'

PyQuery：

In [34]: doc('.item-1>a')[0].text Out[34]: 'second item'

re:

In [35]: re.findall(r'<li class="item-1"><a href="link2.html">(.*?)</a></li>', html)[0] Out[35]: 'second item'

匹配第五個li標籤的href屬性：

Xpath：

In [36]: text.xpath('//li[@class="item-0"]/a/@href')[0] Out[36]: 'link5.html'

BeautifulSoup：

In [52]:  soup.find_all(attrs={'class': 'item-0'}) Out[52]: [<li class="item-0">first item</li>, <li class="item-0 active"><a href="link3.html"><span class="bold">third item</span></a></li>, <li class="item-0"><a href="link5.html">fifth item</a></li>] In [53]: soup.find_all(attrs={'class': 'item-0'})[-1].a.attrs['href'] Out[53]: 'link5.html'

PyQuery：

In [75]: [i.attr.href for i in doc('.item-0 a').items()][1] Out[75]: 'link5.html'

re:

In [95]: re.findall(r'<li class="item-0" ><a href="(.*?)">fifth item</a></li>',html)[0] Out[95]: 'link5.html'

示例3

<li><span class="label">房屋用途</span>普通住宅</li>

分別獲取出房屋用途和普通住宅

Xpath：

In [47]: text.xpath('//li/span/text()')[0] Out[47]: '房屋用途' In [49]: text.xpath('//li/text()')[0] Out[49]: '普通住宅'

BeautifulSoup：

In [65]: soup.span.string Out[65]: '房屋用途' In [69]: soup.li.contents[1] # contents 獲取直接子節點
Out[69]: '普通住宅'

PyQuery：

In [70]: doc('li span').text() Out[70]: '房屋用途' In [75]: doc('li .label')[0].tail Out[75]: '普通住宅'

re: 略

示例4

<div class="unitPrice">
    <span class="unitPriceValue">26667<i>元/平米</i></span>
</div>

分別獲取26667和元/平米

Xpath:

In [81]: text.xpath('//div[@class="unitPrice"]/span/text()')[0] Out[81]: '26667' In [82]: text.xpath('//div[@class="unitPrice"]/span/i/text()')[0] Out[82]: '元/平米'

BeautifulSoup:

In [97]: [i for i in soup.find('div', class_="unitPrice").strings] Out[97]: ['\n', '26667', '元/平米', '\n'] In [98]: [i for i in soup.find('div', class_="unitPrice").strings][1] Out[98]: '26667' In [99]: [i for i in soup.find('div', class_="unitPrice").strings][2] Out[99]: '元/平米'

PyQuery:

In [109]: doc('.unitPrice .unitPriceValue')[0].text Out[109]: '26667' In [110]: doc('.unitPrice .unitPriceValue i')[0].text Out[110]: '元/平米'

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