用scrapy进行网页抓取

最近用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:

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 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()

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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:

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 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):

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 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'])
             )

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完成之后在setting.py中添加该pipeline:

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 ITEM_PIPELINES = ['myproject.pipelines.MySQLStorePipeline']

?最后运行scrapy crawl bookspider就开始抓取了

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