Many languages can crawl, but crawlers based on python are more concise and convenient. Crawlers have also become an essential part of the python language. There are also many ways to parse crawlers. The previous article told you about the fourth method of parsing crawlers: PyQuery. Today I bring you another method, XPath.
The basic use of xpath for python crawlers
1. Introduction
XPath is a language for finding information in XML documents. XPath can be used to traverse elements and attributes in XML documents. XPath is a major element of the W3C XSLT standard, and both XQuery and XPointer are built on XPath expressions.
2. Installation
pip3 install lxml
3. Use
1 , Import
from lxml import etree
2. Basic usage
from lxml import etree
wb_data = """ <div> <ul> <li class="item-0"><a href="link1.html">first item</a></li> <li class="item-1"><a href="link2.html">second item</a></li> <li class="item-inactive"><a href="link3.html">third item</a></li> <li class="item-1"><a href="link4.html">fourth item</a></li> <li class="item-0"><a href="link5.html">fifth item</a> </ul> </div> """ html = etree.HTML(wb_data) print(html) result = etree.tostring(html) print(result.decode("utf-8"))
From the results below, our printer html is actually a python object, and etree.tostring(html) is The basic writing method of html in Buquanli completes the tags that are missing arms and legs.
<Element html at 0x39e58f0> <html><body><div> <ul> <li class="item-0"><a href="link1.html">first item</a></li> <li class="item-1"><a href="link2.html">second item</a></li> <li class="item-inactive"><a href="link3.html">third item</a></li> <li class="item-1"><a href="link4.html">fourth item</a></li> <li class="item-0"><a href="link5.html">fifth item</a> </li></ul> </div> </body></html>
3. Get the content of a certain tag (basic use). Note that to get all the content of the a tag, there is no need to add a forward slash after a, otherwise an error will be reported.
Writing method one
html = etree.HTML(wb_data) html_data = html.xpath('/html/body/div/ul/li/a') print(html) for i in html_data: print(i.text)
<Element html at 0x12fe4b8> first item second item third item fourth item fifth item
Writing method two (Directly in the tag where you need to find the content Just add a /text() after it)
html = etree.HTML(wb_data) html_data = html.xpath('/html/body/div/ul/li/a/text()') print(html) for i in html_data: print(i)
<Element html at 0x138e4b8> first item second item third item fourth item fifth item4. Open and read the html file
#使用parse打开html的文件 html = etree.parse('test.html') html_data = html.xpath('//*')<br>#打印是一个列表,需要遍历 print(html_data) for i in html_data: print(i.text)
html = etree.parse('test.html') html_data = etree.tostring(html,pretty_print=True) res = html_data.decode('utf-8') print(res)Print:
<div> <ul> <li class="item-0"><a href="link1.html">first item</a></li> <li class="item-1"><a href="link2.html">second item</a></li> <li class="item-inactive"><a href="link3.html">third item</a></li> <li class="item-1"><a href="link4.html">fourth item</a></li> <li class="item-0"><a href="link5.html">fifth item</a></li> </ul> </div> 5. Print the attributes of the a tag under the specified path (you can get a certain value by traversing The value of an attribute, find the content of the tag)
html = etree.HTML(wb_data) html_data = html.xpath('/html/body/div/ul/li/a/@href') for i in html_data: print(i)Print:
link1.html link2.html link3.html link4.html link5.html6. We know that we use xpath to get ElementTree objects one by one. So if you need to find content, you also need to traverse the list of data. Find the content of the a tag attribute equal to link2.html under the absolute path.
html = etree.HTML(wb_data) html_data = html.xpath('/html/body/div/ul/li/a[@href="link2.html"]/text()') print(html_data) for i in html_data: print(i)Print: ['second item']second item
7. Above we found all absolute paths (each one is searched from the root), below we find relative paths, for example, find the a tag content under all li tags.
html = etree.HTML(wb_data) html_data = html.xpath('//li/a/text()') print(html_data) for i in html_data: print(i)Print:
['first item', 'second item', 'third item', 'fourth item', 'fifth item'] first item second item third item fourth item fifth item8. Above we used the absolute path to find the attributes of all a tags that are equal to the href attribute value, using It is /---absolute path. Next we use relative path to find the value of the href attribute under the a tag under the li tag under the l relative path. Note that double // is required after the a tag.
html = etree.HTML(wb_data) html_data = html.xpath('//li/a//@href') print(html_data) for i in html_data: print(i)Print:
['link1.html', 'link2.html', 'link3.html', 'link4.html', 'link5.html'] link1.html link2.html link3.html link4.html link5.html
9. The method of checking specific attributes under relative paths is similar to that under absolute paths, or it can be said to be the same.
html = etree.HTML(wb_data) html_data = html.xpath('//li/a[@href="link2.html"]') print(html_data) for i in html_data: print(i.text)Print:
[<Element a at 0x216e468>] second item
10、查找最后一个li标签里的a标签的href属性
html = etree.HTML(wb_data) html_data = html.xpath('//li[last()]/a/text()') print(html_data) for i in html_data: print(i)
打印:
['fifth item'] fifth item
11、查找倒数第二个li标签里的a标签的href属性
html = etree.HTML(wb_data) html_data = html.xpath('//li[last()-1]/a/text()') print(html_data) for i in html_data: print(i)
打印:
['fourth item'] fourth item
12、如果在提取某个页面的某个标签的xpath路径的话,可以如下图:
//*[@id="kw"]
解释:使用相对路径查找所有的标签,属性id等于kw的标签。
#!/usr/bin/env python # -*- coding:utf-8 -*- from scrapy.selector import Selector, HtmlXPathSelector from scrapy.http import HtmlResponse html = """<!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title></title> </head> <body> <ul> <li><a id='i1' href="link.html">first item</a></li> <li><a id='i2' href="llink.html">first item</a></li> <li><a href="llink2.html">second item<span>vv</span></a></li> </ul> <div><a href="llink2.html">second item</a></div> </body> </html> """ response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8') # hxs = HtmlXPathSelector(response) # print(hxs) # hxs = Selector(response=response).xpath('//a') # print(hxs) # hxs = Selector(response=response).xpath('//a[2]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first() # print(hxs) # ul_list = Selector(response=response).xpath('//body/ul/li') # for item in ul_list: # v = item.xpath('./a/span') # # 或 # # v = item.xpath('a/span') # # 或 # # v = item.xpath('*/a/span') # print(v)
The above is the detailed content of Crawler parsing method five: XPath. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

WebStorm Mac version
Useful JavaScript development tools