Does using scrapy-splash significantly affect scraping speed?

10,553

It depends on the amount of javascript present on the page.

You must know that to render all the javascript the splash takes some time and the python application proceeds without waiting for the rendering to be complete. So sometimes splash is also not able to do it.

  • You can explicitly put a wait for rendering as it needs some time generally.
  • Also it is a good practice to put up some wait.

Here,

import scrapy
from scrapy_splash import SplashRequest

yield scrapy.Request(url, callback=self.parse, meta={'splash':{'args':{'wait':'25'},'endpoint':'render.html'}})

or

import scrapy
from scrapy_splash import SplashRequest

yield SplashRequest(url, self.parse, endpoint='render.html',
        args={'wait': 5, 'html' : 1 } ) 

Between scrapy and selenium

Selenium is only used to automate web browser interaction, Scrapy is used to download HTML, process data and save it(whole web crawling framework).

Talking about scraping I would recommend scrapy and if the problem is javascript.

  • Scrapy already has its own official project for javascript called scrapy-splash
  • Also, you can create new instance of webdriver from Selenium in the scrapy spider, do some work, extract the data, and then close it after all work done.
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hsy
Author by

hsy

Updated on June 03, 2022

Comments

  • hsy
    hsy almost 2 years

    So far, I have been using just scrapy and writing custom classes to deal with websites using ajax.

    But if I were to use scrapy-splash, which from what I understand, scrapes the rendered html after javascript, will the speed of my crawler be affected significantly?

    What would be the comparison between time it takes to scrape a vanilla html page with scrapy vs javascript rendered html with scrapy-splash?

    And lastly, how do scrapy-splash and Selenium compare?

  • mgrollins
    mgrollins over 5 years
    Thank you for answering @Nandesh! The question has been closed as broad, but your answer covered all the important points for me!
  • Nandesh
    Nandesh over 5 years
    @mgrollins always :)