How to implement web crawler in python
How to implement a web crawler in python: 1. Use the get method in the request library to request the web page content of the url; 2. The [find()] and [find_all()] methods can traverse the html file and extract Specify information.
How to implement a web crawler in python:
The first step: crawling
Use the get method in the request library to request the web page content of the url
Write code
[root@localhost demo]# touch demo.py [root@localhost demo]# vim demo.py
#web爬虫学习 -- 分析 #获取页面信息 #输入:url #处理:request库函数获取页面信息,并将网页内容转换成为人能看懂的编码格式 #输出:爬取到的内容 import requests def getHTMLText(url): try: r = requests.get( url, timeout=30 ) r.raise_for_status() #如果状态码不是200,产生异常 r.encoding = 'utf-8' #字符编码格式改成 utf-8 return r.text except: #异常处理 return " error " url = "http://www.baidu.com" print( getHTMLText(url) )
[root@localhost demo]# python3 demo.py
Step 2: Analysis
Use the BeautifulSoup class in the bs4 library to generate an object. The find() and find_all() methods can traverse this html file and extract specified information.
Writing code
[root@localhost demo]# touch demo1.py [root@localhost demo]# vim demo1.py #web爬虫学习 -- 分析 #获取页面信息 #输入:url #处理:request库获取页面信息,并从爬取到的内容中提取关键信息 #输出:打印输出提取到的关键信息 import requests from bs4 import BeautifulSoup import re def getHTMLText(url): try: r = requests.get( url, timeout=30 ) r.raise_for_status() #如果状态码不是200,产生异常 r.encoding = 'utf-8' #字符编码格式改成 utf-8 return r.text except: #异常处理 return " error " def findHTMLText(text): soup = BeautifulSoup( text, "html.parser" ) #返回BeautifulSoup对象 return soup.find_all(string=re.compile( '百度' )) #结合正则表达式,实现字符串片段匹配 url = "http://www.baidu.com" text = getHTMLText(url) #获取html文本内容 res = findHTMLText(text) #匹配结果 print(res) #打印输出
[root@localhost demo]# python3 demo1.py
##Related free learning recommendations: python video tutorial
The above is the detailed content of How to implement web crawler in python. For more information, please follow other related articles on the PHP Chinese website!

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

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

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

Hot Topics



PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

VS Code is available on Mac. It has powerful extensions, Git integration, terminal and debugger, and also offers a wealth of setup options. However, for particularly large projects or highly professional development, VS Code may have performance or functional limitations.

The key to running Jupyter Notebook in VS Code is to ensure that the Python environment is properly configured, understand that the code execution order is consistent with the cell order, and be aware of large files or external libraries that may affect performance. The code completion and debugging functions provided by VS Code can greatly improve coding efficiency and reduce errors.
