用scrapy来进行网页抓取,对于pythoner来说它用起来非常方便,详细文档在这里:http://doc.scrapy.org/en/0.14/index.html

要想利用scrapy来抓取网页信息,需要先新建一个工程,scrapy startproject myproject

工程建立好后,会有一个myproject/myproject的子目录,里面有item.py(由于你要抓取的东西的定义),pipeline.py(用于处理抓取后的数据,可以保存数据库,或是其他),然后是spiders文件夹,可以在里面编写爬虫的脚本.

这里以爬取某网站的书籍信息为例:

item.py如下:

from scrapy.item import Item, Field    class BookItem(Item):      # define the fields for your item here like:      name = Field()      publisher = Field()      publish_date = Field()      price = Field()

我们要抓取的东西都在上面定义好了,分别是名字,出版商,出版日期,价格,

下面就要写爬虫去网战抓取信息了,

spiders/book.py如下:

from urlparse import urljoin  import simplejson    from scrapy.http import Request  from scrapy.contrib.spiders import CrawlSpider, Rule  from scrapy.contrib.linkextractors.sgml import SgmlLinkExtractor  from scrapy.selector import HtmlXPathSelector    from myproject.items import BookItem    class BookSpider(CrawlSpider):      name = 'bookspider'      allowed_domains = ['test.com']      start_urls = [          "http://test_url.com",   #这里写开始抓取的页面地址(这里网址是虚构的,实际使用时请替换)      ]      rules = (          #下面是符合规则的网址,但是不抓取内容,只是提取该页的链接(这里网址是虚构的,实际使用时请替换)          Rule(SgmlLinkExtractor(allow=(r'http://test_url/test?page_index=\d+'))),          #下面是符合规则的网址,提取内容,(这里网址是虚构的,实际使用时请替换)          Rule(SgmlLinkExtractor(allow=(r'http://test_rul/test?product_id=\d+')), callback="parse_item"),      )                  def parse_item(self, response):          hxs = HtmlXPathSelector(response)          item = BookItem()          item['name'] = hxs.select('//div[@class="h1_title book_head"]/h1/text()').extract()[0]          item['author'] = hxs.select('//div[@class="book_detailed"]/p[1]/a/text()').extract()          publisher = hxs.select('//div[@class="book_detailed"]/p[2]/a/text()').extract()          item['publisher'] = publisher and publisher[0] or ''          publish_date = hxs.select('//div[@class="book_detailed"]/p[3]/text()').re(u"[\u2e80-\u9fffh]+\uff1a([\d-]+)")          item['publish_date'] = publish_date and publish_date[0] or ''          prices = hxs.select('//p[@class="price_m"]/text()').re("(\d*\.*\d*)")          item['price'] = prices and prices[0] or ''          return item

然后信息抓取后,需要保存,这时就需要写pipelines.py了(用于scapy是用的twisted,所以具体的数据库操作可以看twisted的资料,这里只是简单介绍如何保存到数据库中):

from scrapy import log  #from scrapy.core.exceptions import DropItem  from twisted.enterprise import adbapi  from scrapy.http import Request  from scrapy.exceptions import DropItem  from scrapy.contrib.pipeline.images import ImagesPipeline  import time  import MySQLdb  import MySQLdb.cursors      class MySQLStorePipeline(object):        def __init__(self):          self.dbpool = adbapi.ConnectionPool('MySQLdb',                  db = 'test',                  user = 'user',                  passwd = '******',                  cursorclass = MySQLdb.cursors.DictCursor,                  charset = 'utf8',                  use_unicode = False          )        def process_item(self, item, spider):                    query = self.dbpool.runInteraction(self._conditional_insert, item)                    query.addErrback(self.handle_error)          return item          def _conditional_insert(self, tx, item):          if item.get('name'):              tx.execute(\                  "insert into book (name, publisher, publish_date, price ) \                   values (%s, %s, %s, %s)",                  (item['name'],  item['publisher'], item['publish_date'],                   item['price'])              )

完成之后在setting.py中添加该pipeline:

ITEM_PIPELINES = ['myproject.pipelines.MySQLStorePipeline']

最后运行scrapy crawl bookspider就开始抓取了

参考:www.chengxuyuans.com

http://www.chengxuyuans.com/Python/39302.html

来自：http://blog.csdn.net/huaweitman/article/details/9613999