Make Scrapy follow links and collect data

# -*- coding: utf-8 -*-
import scrapy

# item class included here 
class DmozItem(scrapy.Item):
    # define the fields for your item here like:
    link = scrapy.Field()
    attr = scrapy.Field()

class DmozSpider(scrapy.Spider):
    name = "dmoz"
    allowed_domains = [""]
    start_urls = [

    BASE_URL = ''

    def parse(self, response):
        links = response.xpath('//a[@class="hdrlnk"]/@href').extract()
        for link in links:
            absolute_url = self.BASE_URL + link
            yield scrapy.Request(absolute_url, callback=self.parse_attr)

    def parse_attr(self, response):
        item = DmozItem()
        item["link"] = response.url
        item["attr"] = "".join(response.xpath("//p[@class='attrgroup']//text()").extract())
        return item


Use Google’s Cache to crawl sites

Some websites implement certain measures to prevent bots from crawling them, with varying degrees of sophistication. Getting around those measures can be difficult and tricky, and may sometimes require special infrastructure. Please consider contacting commercial support if in doubt.

Here are some tips to keep in mind when dealing with these kinds of sites:

  • rotate your user agent from a pool of well-known ones from browsers (google around to get a list of them)
  • disable cookies (see COOKIES_ENABLED) as some sites may use cookies to spot bot behaviour
  • use download delays (2 or higher). See DOWNLOAD_DELAY setting.
  • if possible, use Google cache to fetch pages, instead of hitting the sites directly
  • use a pool of rotating IPs. For example, the free Tor project or paid services like ProxyMesh. An open source alternative is scrapoxy, a super proxy that you can attach your own proxies to.
  • use a highly distributed downloader that circumvents bans internally, so you can just focus on parsing clean pages. One example of such downloaders is Crawlera