Common Practices

This section documents common practices when using Scrapy. These are things that cover many topics and don’t often fall into any other specific section.

Run Scrapy from a script

You can use the API to run Scrapy from a script, instead of the typical way of running Scrapy via scrapy crawl.

Remember that Scrapy is built on top of the Twisted asynchronous networking library, so you need run it inside the Twisted reactor.

Note that you will also have to shutdown the Twisted reactor yourself after the spider is finished. This can be achieved by connecting a handler to the signals.spider_closed signal.

What follows is a working example of how to do that, using the testspiders project as example.

from twisted.internet import reactor
from scrapy.crawler import Crawler
from scrapy import log, signals
from testspiders.spiders.followall import FollowAllSpider
from scrapy.utils.project import get_project_settings

spider = FollowAllSpider(domain='')
settings = get_project_settings()
crawler = Crawler(settings)
crawler.signals.connect(reactor.stop, signal=signals.spider_closed)
log.start() # the script will block here until the spider_closed signal was sent

Running multiple spiders in the same process

By default, Scrapy runs a single spider per process when you run scrapy crawl. However, Scrapy supports running multiple spiders per process using the internal API.

Here is an example, using the testspiders project:

from twisted.internet import reactor
from scrapy.crawler import Crawler
from scrapy import log
from testspiders.spiders.followall import FollowAllSpider
from scrapy.utils.project import get_project_settings

def setup_crawler(domain):
    spider = FollowAllSpider(domain=domain)
    settings = get_project_settings()
    crawler = Crawler(settings)

for domain in ['', '']:

Distributed crawls

Scrapy doesn’t provide any built-in facility for running crawls in a distribute (multi-server) manner. However, there are some ways to distribute crawls, which vary depending on how you plan to distribute them.

If you have many spiders, the obvious way to distribute the load is to setup many Scrapyd instances and distribute spider runs among those.

If you instead want to run a single (big) spider through many machines, what you usually do is partition the urls to crawl and send them to each separate spider. Here is a concrete example:

First, you prepare the list of urls to crawl and put them into separate files/urls:

Then you fire a spider run on 3 different Scrapyd servers. The spider would receive a (spider) argument part with the number of the partition to crawl:

curl -d project=myproject -d spider=spider1 -d part=1
curl -d project=myproject -d spider=spider1 -d part=2
curl -d project=myproject -d spider=spider1 -d part=3

Avoiding getting banned

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 kind 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
  • 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

If you are still unable to prevent your bot getting banned, consider contacting commercial support.

Dynamic Creation of Item Classes

For applications in which the structure of item class is to be determined by user input, or other changing conditions, you can dynamically create item classes instead of manually coding them.

from scrapy.item import DictItem, Field

def create_item_class(class_name,field_list):
    field_dict = {}
    for field_name in field_list:
        field_dict[field_name] = Field()

    return type(class_name,DictItem,field_dict)