爬虫是一段自动抓取互联息的程序。它的价值是互联网数据为我所有。利用爬取到的数据，可以做很多的事情如：可以进行数据统计，对比；可以利用爬取的数据做某一方面的app；也可以利用爬取的数据做一个新闻阅读器等等。
爬虫架构
1）URL管理器
2）网页下载器
3）网页分析器
4）爬虫调用器
5）价值数据使用
爬虫实现
1）调度器实现
# coding:utf-8 import url_manager import html_downloader import html_parser import html_outputer import url_manager class SpiderMain(object): def __init__(self): self.urls = url_manager.UrlManager() self.downloader = html_downloader.HtmlDownloader() self.parser = html_parser.HtmlParser() self.outputer = html_outputer.HtmlOutputer() def craw(self, root_url): count = 1 self.urls.add_new_url(root_url) while self.urls.has_new_url(): try: new_url = self.urls.get_new_url() print "craw %d : %s" % (count, new_url) html_cont = self.downloader.download(new_url) new_urls, new_data = self.parser.parse(new_url, html_cont) self.urls.add_new_urls(new_urls) self.outputer.collect_data(new_data) if count == 1000: break count = count + 1 except: print "craw failed" self.outputer.output_html() if __name__ == "__main__": root_url = "http://baike.baidu.com/view/21087.htm" obj_spider = SpiderMain() obj_spider.craw(root_url)
2）URL管理器实现
class UrlManager(object): def __init__(self): self.new_urls = set() self.old_urls = set() def add_new_url(self, url): if url is None: return if url not in self.new_urls and url not in self.old_urls: self.new_urls.add(url) def add_new_urls(self, urls): if urls is None or len(urls) == 0: return for url in urls: self.add_new_url(url) def has_new_url(self): return len(self.new_urls) != 0 def get_new_url(self): new_url = self.new_urls.pop() self.old_urls.add(new_url) return new_url
3）URL下载器实现
import urllib2 class HtmlDownloader(object): def download(self, url): if url is None: return None response = urllib2.urlopen(url) if response.getcode() != 200: return None return response.read()
4）URL解析器实现
from bs4 import BeautifulSoup
import re
import urlparse
class HtmlParser(object):
def _get_new_urls(self, page_url, soup):
new_urls = set()
links = soup.find_all('a', href=re.compile(r"/view/d+.htm"))
for link in links:
new_url = link['href']
new_full_url = urlparse.urljoin(page_url, new_url)
new_urls.add(new_full_url)
return new_urls
def _get_new_data(self, page_url, soup):
res_data = {}
res_data['url'] = page_url
title_node = soup.find('dd', class_="lemmaWgt-lemmaTitle-title").find("h1")
res_data['title'] = title_node.get_text()
summary_node = soup.find('div', class_="lemma-summary")
res_data['summary'] = summary_node.get_text()
return res_data
def parse(self, page_url, html_cont):
if page_url is None or html_cont is None:
return
soup = BeautifulSoup(html_cont, 'html.parser', from_encoding='utf-8')
new_urls = self._get_new_urls(page_url, soup)
new_data = self._get_new_data(page_url, soup)
return new_urls, new_data5）价值数据输出显示
# coding:utf-8
class HtmlOutputer(object):
def __init__(self):
self.datas = []
def collect_data(self, data):
if data is None:
return
self.datas.append(data)
def output_html(self):
fout = open('output.html', 'w')
fout.write("<html>")
fout.write("<meta charset="UTF-8">")
fout.write("<body>")
fout.write("<table>")
for data in self.datas:
fout.write("<tr>")
fout.write("<td>%s</td>" % data['url'])
fout.write("<td>%s</td>" % data['title'].encode('utf-8'))
fout.write("<td>%s</td>" % data['summary'].encode('utf-8'))
fout.write("</tr>")
fout.write("</table>")
fout.write("</body>")
fout.write("</html>")
fout.close()执行
本爬虫为爬取百度百科与Python关键字相关的1000个静态网页，对网页中的数据，主要提取关键词和摘要信息，并将爬取的信息以HTML文件的方式存储，之后利用浏览器打开即可实现访问。
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