Java中怎么抓取网页中的图片

通过httpclient来爬取网站内容，分析当前内容页中的图片‘规则’

抓取一般都是模拟浏览器访问目标网页，通过返回的页面html代码进行分析自己需要的数据

查找规则，例如你爬取的网页 ，看到当前页面显示的图片格式如下<img src="http://www.baidu.com/img/20101025_user.png">

通过解析爬取的网页源代码（html）进行字符串的 *** 作即可，现在有相应的第三方jar包可以帮你更快的完成这部分工作，例如htmlpaser，获取到对应的地址，然后进行保存或下载。

你可以搜索，java爬虫(httpclient)和htmlpaser做更多的了解。

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\x0awhile (continueCrawling()) { \x0d\x0aCrawlerUrl url = getNextUrl()//获取待爬取队列中的下一个URL\x0d\x0aif (url != null) { \x0d\x0aprintCrawlInfo() \x0d\x0aString 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\x0aif (isContentRelevant(content, this.regexpSearchPattern)) { \x0d\x0asaveContent(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\x0aCollection urlStrings = extractUrls(content, url)\x0d\x0aaddUrlsToUrlQueue(url, urlStrings)\x0d\x0a} else { \x0d\x0aSystem.out.println(url + " is not relevant ignoring ...")\x0d\x0a} \x0d\x0a\x0d\x0a//延时防止被对方屏蔽\x0d\x0aThread.sleep(this.delayBetweenUrls)\x0d\x0a} \x0d\x0a} \x0d\x0acloseOutputStream()\x0d\x0a}\x0d\x0aprivate CrawlerUrl getNextUrl() throws Throwable { \x0d\x0aCrawlerUrl nextUrl = null\x0d\x0awhile ((nextUrl == null) &&(!urlQueue.isEmpty())) { \x0d\x0aCrawlerUrl 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\x0aif (doWeHavePermissionToVisit(crawlerUrl) \x0d\x0a&&(!isUrlAlreadyVisited(crawlerUrl)) \x0d\x0a&&isDepthAcceptable(crawlerUrl)) { \x0d\x0anextUrl = crawlerUrl\x0d\x0a// System.out.println("Next url to be visited is " + nextUrl)\x0d\x0a} \x0d\x0a} \x0d\x0areturn 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\x0aHttpClient client = new DefaultHttpClient()\x0d\x0aHttpGet httpGet = new HttpGet(url.getUrlString())\x0d\x0aStringBuffer strBuf = new StringBuffer()\x0d\x0aHttpResponse response = client.execute(httpGet)\x0d\x0aif (HttpStatus.SC_OK == response.getStatusLine().getStatusCode()) { \x0d\x0aHttpEntity entity = response.getEntity()\x0d\x0aif (entity != null) { \x0d\x0aBufferedReader reader = new BufferedReader( \x0d\x0anew InputStreamReader(entity.getContent(), "UTF-8"))\x0d\x0aString line = null\x0d\x0aif (entity.getContentLength() >0) { \x0d\x0astrBuf = new StringBuffer((int) entity.getContentLength())\x0d\x0awhile ((line = reader.readLine()) != null) { \x0d\x0astrBuf.append(line)\x0d\x0a} \x0d\x0a} \x0d\x0a} \x0d\x0aif (entity != null) { \x0d\x0ansumeContent()\x0d\x0a} \x0d\x0a} \x0d\x0a//将url标记为已访问 \x0d\x0amarkUrlAsVisited(url)\x0d\x0areturn strBuf.toString()\x0d\x0a}\x0d\x0apublic static boolean isContentRelevant(String content, \x0d\x0aPattern regexpPattern) { \x0d\x0aboolean retValue = false\x0d\x0aif (content != null) { \x0d\x0a//是否符合正则表达式的条件 \x0d\x0aMatcher m = regexpPattern.matcher(content.toLowerCase())\x0d\x0aretValue = m.find()\x0d\x0a} \x0d\x0areturn retValue\x0d\x0a}\x0d\x0apublic List extractUrls(String text, CrawlerUrl crawlerUrl) { \x0d\x0aMap urlMap = new HashMap()\x0d\x0aextractHttpUrls(urlMap, text)\x0d\x0aextractRelativeUrls(urlMap, text, crawlerUrl)\x0d\x0areturn new ArrayList(urlMap.keySet())\x0d\x0a} \x0d\x0aprivate void extractHttpUrls(Map urlMap, String text) { \x0d\x0aMatcher m = (text)\x0d\x0awhile (m.find()) { \x0d\x0aString url = m.group()\x0d\x0aString[] terms = url.split("a href=\"")\x0d\x0afor (String term : terms) { \x0d\x0a// System.out.println("Term = " + term)\x0d\x0aif (term.startsWith("http")) { \x0d\x0aint index = term.indexOf("\"")\x0d\x0aif (index >0) { \x0d\x0aterm = term.substring(0, index)\x0d\x0a} \x0d\x0aurlMap.put(term, term)\x0d\x0aSystem.out.println("Hyperlink: " + term)\x0d\x0a} \x0d\x0a} \x0d\x0a} \x0d\x0a} \x0d\x0aprivate void extractRelativeUrls(Map urlMap, String text, \x0d\x0aCrawlerUrl crawlerUrl) { \x0d\x0aMatcher m = relativeRegexp.matcher(text)\x0d\x0aURL textURL = crawlerUrl.getURL()\x0d\x0aString host = textURL.getHost()\x0d\x0awhile (m.find()) { \x0d\x0aString url = m.group()\x0d\x0aString[] terms = url.split("a href=\"")\x0d\x0afor (String term : terms) { \x0d\x0aif (term.startsWith("/")) { \x0d\x0aint index = term.indexOf("\"")\x0d\x0aif (index >0) { \x0d\x0aterm = term.substring(0, index)\x0d\x0a} \x0d\x0aString s = //" + host + term\x0d\x0aurlMap.put(s, s)\x0d\x0aSystem.out.println("Relative url: " + s)\x0d\x0a} \x0d\x0a} \x0d\x0a} \x0d\x0a\x0d\x0a}\x0d\x0apublic static void main(String[] args) { \x0d\x0atry { \x0d\x0aString url = ""\x0d\x0aQueue urlQueue = new LinkedList()\x0d\x0aString regexp = "java"\x0d\x0aurlQueue.add(new CrawlerUrl(url, 0))\x0d\x0aNaiveCrawler crawler = new NaiveCrawler(urlQueue, 100, 5, 1000L, \x0d\x0aregexp)\x0d\x0a// boolean allowCrawl = crawler.areWeAllowedToVisit(url)\x0d\x0a// System.out.println("Allowed to crawl: " + url + " " + \x0d\x0a// allowCrawl)\x0d\x0acrawler.crawl()\x0d\x0a} catch (Throwable t) { \x0d\x0aSystem.out.println(t.toString())\x0d\x0at.printStackTrace()\x0d\x0a} \x0d\x0a}

先根据一个链接，抓取该页面；解析该页面，搜取出该页面中有用的链接，根据链接地址循环抓取就OK了；--简单爬行器原理 抓取完文件后还需要一个功能好点的文档解析器来解析出文件中的内容；--文件解析器 再根据关键字（分词器）处理这些页面，建立自己的搜索引擎；--分词器不好解决 我也正在搞这方面 呵呵

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