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:

 

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