Scrape Websites using PhantomJS and CasperJS
What you’ll learn
Be able to Capture, Download and Save Website Data
Understand how to use CasperJS and PhantomJS
- Apply What You’ve Learned to Front-end Testing
- Create Your Own Scripts for Scraping Data
- Have a Better Understanding of Functional Programming
- Helpful to know beginner jQuery syntax
In this course you will learn how to scrape data from web pages using CasperJS.
This course consists of 5 example projects to help you fully understand the powers of the headless browser using the CasperJS API.
What You Will Learn
You will gain a thorough understanding of advanced web scraping concepts and also gain an insight into how to use the CasperJS for Testing DOM manipulation and UI interaction.
What to Expect
- We’ll begin with an overview of how both PhantomJS and CasperJS works along with how to install these frameworks.
- Next, we’ll discuss what our workflow will look like and the options we can pass into a Casper object.
- Then we’ll dive into the meat of this course by working through 5 projects.
The Projects Will Cover
- How to wait for AJAX loaded data to appear before scraping elements
- How to submit forms both for Authorization and when making searches
- How to define navigation Steps – like logging into a site, clicking a button and following links
- How to write and save specified data in tables then output as an .html file or as JSON.
- And how to take screenshots both of full web pages and specific containers
What is PhantomJS?
PhantomJS is a Full Web Stack that employs a headless browser. Phantom gives us the power to perform many interesting actions on a web page, such as: performing page manipulation, simulating user interaction and the ability to dynamically capture and save website data.
What is CasperJS?
CasperJS is a stand-alone framework built on top Phantom and is compatible with most operating systems. The focus of this course will be on the Casper API and we’ll be using this API to write all our web scraping scripts.
What You Should Know
Created by Patrick Schroeder
Last updated 9/2017
Size: 709.88 MB