How to use Java to write scripts to crawl web pages on Linux
How to use Java to write scripts to implement web page crawling on Linux requires specific code examples
Introduction:
In daily work and study, we often Need to get the data on the web page. It is a common way to use Java to write scripts to crawl web pages. This article will introduce how to use Java to write scripts in a Linux environment to crawl web pages, and provide specific code examples.
1. Environment configuration
First, we need to install the Java runtime environment (JRE) and development environment (JDK).
-
Install JRE
Open the terminal on Linux and enter the following command to install:sudo apt-get update sudo apt-get install default-jre
Copy after login Install JDK
Continue in the terminal Enter the following command to install:sudo apt-get install default-jdk
Copy after login
After the installation is complete, use the following command to check whether the installation is successful:
java -version javac -version
2. Use Java to write a web page crawling script
The following is an example of a simple web page crawling script written in Java:
import java.io.BufferedReader; import java.io.IOException; import java.io.InputStreamReader; import java.net.URL; public class WebpageCrawler { public static void main(String[] args) { try { // 定义要抓取的网页地址 String url = "https://www.example.com"; // 创建URL对象 URL webpage = new URL(url); // 打开URL连接 BufferedReader in = new BufferedReader(new InputStreamReader(webpage.openStream())); // 读取网页内容并输出 String inputLine; while ((inputLine = in.readLine()) != null) { System.out.println(inputLine); } // 关闭连接 in.close(); } catch (IOException e) { e.printStackTrace(); } } }
The above code implements web page crawling through Java's input and output streams and URL objects. First, the web page address to be crawled is defined; then, a URL object and a BufferedReader object are created to open the URL connection and read the web page content; finally, the content in the input stream is read through a loop and output to the console.
3. Run the web page crawling script
Compile and run the above Java code to get the web page crawling results.
Compile Java Code
In the terminal, go to the directory where the Java code is located, and then use the following command to compile:javac WebpageCrawler.java
Copy after login
if If the compilation is successful, a WebpageCrawler.class file will be generated in the current directory.
Run the web crawling script
Use the following command to run the web crawling script:java WebpageCrawler
Copy after login
After the execution is completed, the page will be displayed in the terminal Print out the content of the web page.
Summary:
This article introduces how to use Java to write scripts to crawl web pages in a Linux environment, and provides specific code examples. Through simple Java code, we can easily implement web crawling functions, bringing convenience to daily work and learning.
The above is the detailed content of How to use Java to write scripts to crawl web pages on Linux. 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



How to use Docker Desktop? Docker Desktop is a tool for running Docker containers on local machines. The steps to use include: 1. Install Docker Desktop; 2. Start Docker Desktop; 3. Create Docker image (using Dockerfile); 4. Build Docker image (using docker build); 5. Run Docker container (using docker run).

Troubleshooting steps for failed Docker image build: Check Dockerfile syntax and dependency version. Check if the build context contains the required source code and dependencies. View the build log for error details. Use the --target option to build a hierarchical phase to identify failure points. Make sure to use the latest version of Docker engine. Build the image with --t [image-name]:debug mode to debug the problem. Check disk space and make sure it is sufficient. Disable SELinux to prevent interference with the build process. Ask community platforms for help, provide Dockerfiles and build log descriptions for more specific suggestions.

Docker process viewing method: 1. Docker CLI command: docker ps; 2. Systemd CLI command: systemctl status docker; 3. Docker Compose CLI command: docker-compose ps; 4. Process Explorer (Windows); 5. /proc directory (Linux).

PHP is suitable for web development and content management systems, and Python is suitable for data science, machine learning and automation scripts. 1.PHP performs well in building fast and scalable websites and applications and is commonly used in CMS such as WordPress. 2. Python has performed outstandingly in the fields of data science and machine learning, with rich libraries such as NumPy and TensorFlow.

VS Code system requirements: Operating system: Windows 10 and above, macOS 10.12 and above, Linux distribution processor: minimum 1.6 GHz, recommended 2.0 GHz and above memory: minimum 512 MB, recommended 4 GB and above storage space: minimum 250 MB, recommended 1 GB and above other requirements: stable network connection, Xorg/Wayland (Linux)

VS Code is the full name Visual Studio Code, which is a free and open source cross-platform code editor and development environment developed by Microsoft. It supports a wide range of programming languages and provides syntax highlighting, code automatic completion, code snippets and smart prompts to improve development efficiency. Through a rich extension ecosystem, users can add extensions to specific needs and languages, such as debuggers, code formatting tools, and Git integrations. VS Code also includes an intuitive debugger that helps quickly find and resolve bugs in your code.

The reasons for the installation of VS Code extensions may be: network instability, insufficient permissions, system compatibility issues, VS Code version is too old, antivirus software or firewall interference. By checking network connections, permissions, log files, updating VS Code, disabling security software, and restarting VS Code or computers, you can gradually troubleshoot and resolve issues.

VS Code To switch Chinese mode: Open the settings interface (Windows/Linux: Ctrl, macOS: Cmd,) Search for "Editor: Language" settings Select "Chinese" in the drop-down menu Save settings and restart VS Code
