Running scrapy spider programmatically

This post refers to using scrapy version 0.24.4, if you are using a different version of scrapy then refer scrapy docs for more info. Also this blog post series received a lot of attention so I created a pip package to make it easy to run your scrapy spiders. Please check the project on github.
Jan 24, 2015 • 4 minutes to read • Last Updated: Oct 25, 2017

I wanted to share something that I have been working on for the past few months, which is, running scrapers with the scrapy framework. I understand that scrapy has existed for many years, but it is still so relevant and useful for me and my team. We were hooked to it and started reading the docs daily on how to get it perfect. There are two ways of running a scrapy spider. You can run a scrapy spider from the command line or using a program.

Today, I am going to illustrate how to use the framework by running it by using its Core API. If you are not familiar with how web scraping works and would like to use scrapy to get you started, then you should definitely look into this tutorial.

What you would need to know before we start are:

  • The Scrapy Spider : It is a python class in the scrapy framework that is responsible for fetching URLs and parsing the information in the page response.

  • Your Custom Spider : It extends the scrapy spider class. We implement the method parse to be able to parse the page response. In the example below DmozSpider is the custom spider.

  • The Scrapy item : It is an object that will act as a dictionary to store all the information you want to parse.

  • The Scrapy Selector : To select elements on the page with an xpath selector or a css selector. In older versions of scrapy you had to import the Selector class but now you can use the selectors on the response object directly.

I am going to use the example from scrapy tutorial to make it easy to understand.

This is what the spider file DmozSpider.py looks like:

import scrapy

class DmozItem(scrapy.Item):
    title = scrapy.Field()
    link = scrapy.Field()
    desc = scrapy.Field()

class DmozSpider(scrapy.Spider):
    name = "dmoz"
    allowed_domains = ["dmoz.org"]
    start_urls = [
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/"
    ]

    def parse(self, response):
        for sel in response.xpath('//ul/li'):
            item = DmozItem()
            item['title'] = sel.xpath('a/text()').extract()
            item['link'] = sel.xpath('a/@href').extract()
            item['desc'] = sel.xpath('text()').extract()
            yield item

To be able to run this spider solely from scrapy core script:

# import dmoz spider class
from DmozSpider import DmozSpider

# scrapy api
from scrapy import signals, log
from twisted.internet import reactor
from scrapy.crawler import Crawler
from scrapy.settings import Settings

def spider_closing(spider):
    """Activates on spider closed signal"""
    log.msg("Closing reactor", level=log.INFO)
    reactor.stop()

log.start(loglevel=log.DEBUG)
settings = Settings()

# crawl responsibly
settings.set("USER_AGENT", "Kiran Koduru (+http://kirankoduru.github.io)")
crawler = Crawler(settings)

# stop reactor when spider closes
crawler.signals.connect(spider_closing, signal=signals.spider_closed)

crawler.configure()
crawler.crawl(DmozSpider())
crawler.start()
reactor.run()

You can also add a pipeline to insert the item into your database by using the ITEMS_PIPELINE in the scrapy settings. I will illustrate that in my next blog post and also how you will be able to run 2 spiders parallely here.

Download Project or View on github