java定向爬虫代码 java编写爬虫程序

JAVA怎么弄爬虫

　以下是一个使用java实现的简单爬虫核心代码：

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public void crawl() throws Throwable {

while (continueCrawling()) {

CrawlerUrl url = getNextUrl(); //获取待爬取队列中的下一个URL

if (url != null) {

printCrawlInfo();

String content = getContent(url); //获取URL的文本信息

//聚焦爬虫只爬取与主题内容相关的网页，这里采用正则匹配简单处理

if (isContentRelevant(content, this.regexpSearchPattern)) {

saveContent(url, content); //保存网页至本地

//获取网页内容中的链接，并放入待爬取队列中

Collection urlStrings = extractUrls(content, url);

addUrlsToUrlQueue(url, urlStrings);

} else {

System.out.println(url + " is not relevant ignoring ...");

}

//延时防止被对方屏蔽

Thread.sleep(this.delayBetweenUrls);

}

}

closeOutputStream();

}

private CrawlerUrl getNextUrl() throws Throwable {

CrawlerUrl nextUrl = null;

while ((nextUrl == null) (!urlQueue.isEmpty())) {

CrawlerUrl crawlerUrl = this.urlQueue.remove();

//doWeHavePermissionToVisit：是否有权限访问该URL，友好的爬虫会根据网站提供的"Robot.txt"中配置的规则进行爬取

//isUrlAlreadyVisited：URL是否访问过，大型的搜索引擎往往采用BloomFilter进行排重，这里简单使用HashMap

//isDepthAcceptable：是否达到指定的深度上限。爬虫一般采取广度优先的方式。一些网站会构建爬虫陷阱（自动生成一些无效链接使爬虫陷入死循环），采用深度限制加以避免

if (doWeHavePermissionToVisit(crawlerUrl)

(!isUrlAlreadyVisited(crawlerUrl))

isDepthAcceptable(crawlerUrl)) {

nextUrl = crawlerUrl;

// System.out.println("Next url to be visited is " + nextUrl);

}

}

return nextUrl;

}

private String getContent(CrawlerUrl url) throws Throwable {

//HttpClient4.1的调用与之前的方式不同

HttpClient client = new DefaultHttpClient();

HttpGet httpGet = new HttpGet(url.getUrlString());

StringBuffer strBuf = new StringBuffer();

HttpResponse response = client.execute(httpGet);

if (HttpStatus.SC_OK == response.getStatusLine().getStatusCode()) {

HttpEntity entity = response.getEntity();

if (entity != null) {

BufferedReader reader = new BufferedReader(

new InputStreamReader(entity.getContent(), "UTF-8"));

String line = null;

if (entity.getContentLength() 0) {

strBuf = new StringBuffer((int) entity.getContentLength());

while ((line = reader.readLine()) != null) {

strBuf.append(line);

}

}

}

if (entity != null) {

nsumeContent();

}

}

//将url标记为已访问

markUrlAsVisited(url);

return strBuf.toString();

}

public static boolean isContentRelevant(String content,

Pattern regexpPattern) {

boolean retValue = false;

if (content != null) {

//是否符合正则表达式的条件

Matcher m = regexpPattern.matcher(content.toLowerCase());

retValue = m.find();

}

return retValue;

}

public List extractUrls(String text, CrawlerUrl crawlerUrl) {

Map urlMap = new HashMap();

extractHttpUrls(urlMap, text);

extractRelativeUrls(urlMap, text, crawlerUrl);

return new ArrayList(urlMap.keySet());

}

private void extractHttpUrls(Map urlMap, String text) {

Matcher m = (text);

while (m.find()) {

String url = m.group();

String[] terms = url.split("a href=\"");

for (String term : terms) {

// System.out.println("Term = " + term);

if (term.startsWith("http")) {

int index = term.indexOf("\"");

if (index 0) {

term = term.substring(0, index);

}

urlMap.put(term, term);

System.out.println("Hyperlink: " + term);

}

}

}

}

private void extractRelativeUrls(Map urlMap, String text,

CrawlerUrl crawlerUrl) {

Matcher m = relativeRegexp.matcher(text);

URL textURL = crawlerUrl.getURL();

String host = textURL.getHost();

while (m.find()) {

String url = m.group();

String[] terms = url.split("a href=\"");

for (String term : terms) {

if (term.startsWith("/")) {

int index = term.indexOf("\"");

if (index 0) {

term = term.substring(0, index);

}

String s = //" + host + term;

urlMap.put(s, s);

System.out.println("Relative url: " + s);

}

}

}

}

public static void main(String[] args) {

try {

String url = "";

Queue urlQueue = new LinkedList();

String regexp = "java";

urlQueue.add(new CrawlerUrl(url, 0));

NaiveCrawler crawler = new NaiveCrawler(urlQueue, 100, 5, 1000L,

regexp);

// boolean allowCrawl = crawler.areWeAllowedToVisit(url);

// System.out.println("Allowed to crawl: " + url + " " +

// allowCrawl);

crawler.crawl();

} catch (Throwable t) {

System.out.println(t.toString());

t.printStackTrace();

}

}

用java编写 网络爬虫求代码和流程 急

import java.awt.*;

import java.awt.event.*;

import java.io.*;

import java.net.*;

import java.util.*;

import java.util.regex.*;

import javax.swing.*;

import javax.swing.table.*;//一个Web的爬行者(注：爬行在这里的意思与抓取，捕获相同)

public class SearchCrawler extends JFrame{

//最大URL保存值

private static final String[] MAX_URLS={"50","100","500","1000"};

//缓存robot禁止爬行列表

private HashMap disallowListCache=new HashMap();

//搜索GUI控件

private JTextField startTextField;

private JComboBox maxComboBox;

private JCheckBox limitCheckBox;

private JTextField logTextField;

private JTextField searchTextField;

private JCheckBox caseCheckBox;

private JButton searchButton;

//搜索状态GUI控件

private JLabel crawlingLabel2;

private JLabel crawledLabel2;

private JLabel toCrawlLabel2;

private JProgressBar progressBar;

private JLabel matchesLabel2;

//搜索匹配项表格列表

private JTable table;

//标记爬行机器是否正在爬行

private boolean crawling;

//写日志匹配文件的引用

private PrintWriter logFileWriter;

//网络爬行者的构造函数

public SearchCrawler(){

//设置应用程序标题栏

setTitle("搜索爬行者");

//设置窗体大小

setSize(600,600);

//处理窗体关闭事件

addWindowListener(new WindowAdapter(){

public void windowClosing(WindowEvent e){

actionExit();

}

});

//设置文件菜单

JMenuBar menuBar=new JMenuBar();

JMenu fileMenu=new JMenu("文件");

fileMenu.setMnemonic(KeyEvent.VK_F);

JMenuItem fileExitMenuItem=new JMenuItem("退出",KeyEvent.VK_X);

fileExitMenuItem.addActionListener(new ActionListener(){

public void actionPerformed(ActionEvent e){

actionExit();

}

});

fileMenu.add(fileExitMenuItem);

menuBar.add(fileMenu);

setJMenuBar(menuBar);

谁有java网络爬虫的代码，经打包给我

/*

最简单的爬虫

*/

import java.io.File;

import java.net.URL;

import java.net.URLConnection;

import java.nio.file.Files;

import java.nio.file.Paths;

import java.util.Scanner;

import java.util.UUID;

import java.util.regex.Matcher;

import java.util.regex.Pattern;

public class DownMM {

public static void main(String[] args) throws Exception {

//out为输出的路径,注意要以\\结尾

String out = "D:\\JSP\\pic\\java\\"; 

try{

File f = new File(out);

if(! f.exists()) {  

f.mkdirs();  

}  

}catch(Exception e){

System.out.println("no");

}

String url = "

Pattern reg = Pattern.compile("img src=\"(.*?)\"");

for(int j=0, i=1; i=10; i++){

URL uu = new URL(url+i);

URLConnection conn = uu.openConnection();

conn.setRequestProperty("User-Agent", "Mozilla/5.0 (Windows NT 6.3; WOW64; Trident/7.0; rv:11.0) like Gecko");

Scanner sc = new Scanner(conn.getInputStream());

Matcher m = reg.matcher(sc.useDelimiter("\\A").next());

while(m.find()){

Files.copy(new URL(m.group(1)).openStream(), Paths.get(out + UUID.randomUUID() + ".jpg"));

System.out.println("已下载:"+j++);

}

}

}

}

Java网络爬虫怎么实现？

网络爬虫是一个自动提取网页的程序，它为搜索引擎从万维网上下载网页，是搜索引擎的重要组成。\x0d\x0a传统爬虫从一个或若干初始网页的URL开始，获得初始网页上的URL，在抓取网页的过程中，不断从当前页面上抽取新的URL放入队列，直到满足系统的一定停止条件。对于垂直搜索来说，聚焦爬虫，即有针对性地爬取特定主题网页的爬虫，更为适合。\x0d\x0a\x0d\x0a以下是一个使用java实现的简单爬虫核心代码：\x0d\x0apublic void crawl() throws Throwable { \x0d\x0a while (continueCrawling()) { \x0d\x0a CrawlerUrl url = getNextUrl(); //获取待爬取队列中的下一个URL \x0d\x0a if (url != null) { \x0d\x0a printCrawlInfo(); \x0d\x0a String content = getContent(url); //获取URL的文本信息 \x0d\x0a \x0d\x0a //聚焦爬虫只爬取与主题内容相关的网页，这里采用正则匹配简单处理 \x0d\x0a if (isContentRelevant(content, this.regexpSearchPattern)) { \x0d\x0a saveContent(url, content); //保存网页至本地 \x0d\x0a \x0d\x0a //获取网页内容中的链接，并放入待爬取队列中 \x0d\x0a Collection urlStrings = extractUrls(content, url); \x0d\x0a addUrlsToUrlQueue(url, urlStrings); \x0d\x0a } else { \x0d\x0a System.out.println(url + " is not relevant ignoring ..."); \x0d\x0a } \x0d\x0a \x0d\x0a //延时防止被对方屏蔽 \x0d\x0a Thread.sleep(this.delayBetweenUrls); \x0d\x0a } \x0d\x0a } \x0d\x0a closeOutputStream(); \x0d\x0a}\x0d\x0aprivate CrawlerUrl getNextUrl() throws Throwable { \x0d\x0a CrawlerUrl nextUrl = null; \x0d\x0a while ((nextUrl == null) (!urlQueue.isEmpty())) { \x0d\x0a CrawlerUrl crawlerUrl = this.urlQueue.remove(); \x0d\x0a //doWeHavePermissionToVisit：是否有权限访问该URL，友好的爬虫会根据网站提供的"Robot.txt"中配置的规则进行爬取 \x0d\x0a //isUrlAlreadyVisited：URL是否访问过，大型的搜索引擎往往采用BloomFilter进行排重，这里简单使用HashMap \x0d\x0a //isDepthAcceptable：是否达到指定的深度上限。爬虫一般采取广度优先的方式。一些网站会构建爬虫陷阱（自动生成一些无效链接使爬虫陷入死循环），采用深度限制加以避免 \x0d\x0a if (doWeHavePermissionToVisit(crawlerUrl) \x0d\x0a (!isUrlAlreadyVisited(crawlerUrl)) \x0d\x0a isDepthAcceptable(crawlerUrl)) { \x0d\x0a nextUrl = crawlerUrl; \x0d\x0a // System.out.println("Next url to be visited is " + nextUrl); \x0d\x0a } \x0d\x0a } \x0d\x0a return nextUrl; \x0d\x0a}\x0d\x0aprivate String getContent(CrawlerUrl url) throws Throwable { \x0d\x0a //HttpClient4.1的调用与之前的方式不同 \x0d\x0a HttpClient client = new DefaultHttpClient(); \x0d\x0a HttpGet httpGet = new HttpGet(url.getUrlString()); \x0d\x0a StringBuffer strBuf = new StringBuffer(); \x0d\x0a HttpResponse response = client.execute(httpGet); \x0d\x0a if (HttpStatus.SC_OK == response.getStatusLine().getStatusCode()) { \x0d\x0a HttpEntity entity = response.getEntity(); \x0d\x0a if (entity != null) { \x0d\x0a BufferedReader reader = new BufferedReader( \x0d\x0a new InputStreamReader(entity.getContent(), "UTF-8")); \x0d\x0a String line = null; \x0d\x0a if (entity.getContentLength() 0) { \x0d\x0a strBuf = new StringBuffer((int) entity.getContentLength()); \x0d\x0a while ((line = reader.readLine()) != null) { \x0d\x0a strBuf.append(line); \x0d\x0a } \x0d\x0a } \x0d\x0a } \x0d\x0a if (entity != null) { \x0d\x0a nsumeContent(); \x0d\x0a } \x0d\x0a } \x0d\x0a //将url标记为已访问 \x0d\x0a markUrlAsVisited(url); \x0d\x0a return strBuf.toString(); \x0d\x0a}\x0d\x0apublic static boolean isContentRelevant(String content, \x0d\x0aPattern regexpPattern) { \x0d\x0a boolean retValue = false; \x0d\x0a if (content != null) { \x0d\x0a //是否符合正则表达式的条件 \x0d\x0a Matcher m = regexpPattern.matcher(content.toLowerCase()); \x0d\x0a retValue = m.find(); \x0d\x0a } \x0d\x0a return retValue; \x0d\x0a}\x0d\x0apublic List extractUrls(String text, CrawlerUrl crawlerUrl) { \x0d\x0a Map urlMap = new HashMap(); \x0d\x0a extractHttpUrls(urlMap, text); \x0d\x0a extractRelativeUrls(urlMap, text, crawlerUrl); \x0d\x0a return new ArrayList(urlMap.keySet()); \x0d\x0a} \x0d\x0aprivate void extractHttpUrls(Map urlMap, String text) { \x0d\x0a Matcher m = (text); \x0d\x0a while (m.find()) { \x0d\x0a String url = m.group(); \x0d\x0a String[] terms = url.split("a href=\""); \x0d\x0a for (String term : terms) { \x0d\x0a // System.out.println("Term = " + term); \x0d\x0a if (term.startsWith("http")) { \x0d\x0a int index = term.indexOf("\""); \x0d\x0a if (index 0) { \x0d\x0a term = term.substring(0, index); \x0d\x0a } \x0d\x0a urlMap.put(term, term); \x0d\x0a System.out.println("Hyperlink: " + term); \x0d\x0a } \x0d\x0a } \x0d\x0a } \x0d\x0a} \x0d\x0aprivate void extractRelativeUrls(Map urlMap, String text, \x0d\x0a CrawlerUrl crawlerUrl) { \x0d\x0a Matcher m = relativeRegexp.matcher(text); \x0d\x0a URL textURL = crawlerUrl.getURL(); \x0d\x0a String host = textURL.getHost(); \x0d\x0a while (m.find()) { \x0d\x0a String url = m.group(); \x0d\x0a String[] terms = url.split("a href=\""); \x0d\x0a for (String term : terms) { \x0d\x0a if (term.startsWith("/")) { \x0d\x0a int index = term.indexOf("\""); \x0d\x0a if (index 0) { \x0d\x0a term = term.substring(0, index); \x0d\x0a } \x0d\x0a String s = //" + host + term; \x0d\x0a urlMap.put(s, s); \x0d\x0a System.out.println("Relative url: " + s); \x0d\x0a } \x0d\x0a } \x0d\x0a } \x0d\x0a \x0d\x0a}\x0d\x0apublic static void main(String[] args) { \x0d\x0a try { \x0d\x0a String url = ""; \x0d\x0a Queue urlQueue = new LinkedList(); \x0d\x0a String regexp = "java"; \x0d\x0a urlQueue.add(new CrawlerUrl(url, 0)); \x0d\x0a NaiveCrawler crawler = new NaiveCrawler(urlQueue, 100, 5, 1000L, \x0d\x0a regexp); \x0d\x0a // boolean allowCrawl = crawler.areWeAllowedToVisit(url); \x0d\x0a // System.out.println("Allowed to crawl: " + url + " " + \x0d\x0a // allowCrawl); \x0d\x0a crawler.crawl(); \x0d\x0a } catch (Throwable t) { \x0d\x0a System.out.println(t.toString()); \x0d\x0a t.printStackTrace(); \x0d\x0a } \x0d\x0a}

java爬虫抓取指定数据

根据java网络编程相关的内容，使用jdk提供的相关类可以得到url对应网页的html页面代码。

针对得到的html代码，通过使用正则表达式即可得到我们想要的内容。

比如，我们如果想得到一个网页上所有包括“java”关键字的文本内容，就可以逐行对网页代码进行正则表达式的匹配。最后达到去除html标签和不相关的内容，只得到包括“java”这个关键字的内容的效果。

从网页上爬取图片的流程和爬取内容的流程基本相同，但是爬取图片的步骤会多一步。

需要先用img标签的正则表达式匹配获取到img标签，再用src属性的正则表达式获取这个img标签中的src属性的图片url，然后再通过缓冲输入流对象读取到这个图片url的图片信息，配合文件输出流将读到的图片信息写入到本地即可。