Source: analyticsindiamag.com
When someone copies and pastes a piece of information from a website, they are essentially doing the same thing that a web scraper does. The only difference is that they do it on a smaller scale. When it comes to web scraping, it uses intelligent automation to acquire information from hundreds, millions – or even billions – of data points. The process is complex as the scraper loads more than one URL, and then loads the entire HTML code for the selected pages. It further gets complicated with advanced scraper rendering whole websites, which includes elements from Javascript and CSS.
Due to its complicated nature, web scraping is extremely difficult to learn. For a learner, it is imperative to identify the right resources through which they can learn data science in an easy manner. In this article, you will find adequate resources to learn web scraping.
Online Courses
As the internet has recently been flooded with tons of online courses, it is the best place to begin your learning journey. A number of online courses – both paid and free versions – can be found. These have been carefully curated so that anyone – be it a beginner or an expert – can learn or upskill themselves. A few courses one can look at are:
- Web Scraping In Python By DataCamp
The course has been put together for those who are interested in exploring the concept of scraping website. The course will provide a strong foundation by teaching the structures of HTML. Also, it will further discuss XPath syntax, selectors, CSS locators, and responses. The techniques taught in the course can be applied to Scrapy as well as other Python libraries.
The course can be completed in four hours, with access to the first few sections made free.
- Web Scraping In Nodejs By Udemy
The course gets a learner started with Nodejs, Puppeteer, Cheerio, and teaches other techniques to scrape a website. One gets to learn how to reverse engineer sites and find their APIs. The classes create a scraper which iterates every hour, and the extracted outputs are saved in MongoDB or CSV files.
The course can be completed in 10 hours at a nominal charge of Rs 700.
Books
Although the internet provides a sea of knowledge, books are important as well. When it comes to web scraping, several books have been penned down by experts that are related to Python web scraping, PHP web scraping, Java web scraping, and more. Most of these can be found in the form of ebooks, and some are also available for free. Here is a list that one can check:
- Web Scraping With Python By Richard Lawson
The book has been authored by a real-life web scraping practitioner who has put together a web scraping process, real-life problems and solutions. The book consists of a detailed chapter on Scrapy, a chapter on how to deal with CAPTCHA, handling dynamics, and on concurrent downloads. It also covers other details such as parsing scraped pages and caching. The book has been authored for anyone who has a basic knowledge of Python.
- Web Bots, Spiders, And Screen Scrapers By Michael Schrenk
This can teach you how to interpret and analyze the data one pulls from a website along with automating purchases. The codes provided in the book are straightforward, and the book can be used by people who are new to web scraping.
- Guide To Web Scraping With PHP By Matthew Turland
Penned down by scraping expert Mathew Turland, the book offers different ways to scrape the web by using different kinds of the frameworks. The book has been recommended as the best one for those who are new to PHP scraping and contains working code examples. It also comes with comparisons for a few different libraries that can be used to parse and scrape HTML code.
Videos
Videos are an excellent source to learn a new subject since it allows a learner to get a visual understanding, which can be an easier way to learn. It also allows a learner to watch the tutorial numerous times to understand the process better. There are several videos on Youtube and a few channels which are dedicated to web scraping. To begin with web scraping, one can take a look at the given links:
- Intro to Web Scraping with Python and Beautiful Soup
Produced by channel Data Science Dojo, the video teaches how to set Anaconda, Beautiful Soup and Urllib. The video shows how to parse a web page into a data file (CSV).
- Web Scraping with Python by Edureka
The video is created for beginners. It explains the fundamentals of web scraping and provides a demo of scraping some data from a website. It gives a brief description of the libraries used along with a definition of web scraping and its need.
Blogs
Since web scraping has become a need of the hour for companies from all industries, several blogs have emerged. These explain web scraping in a clear language. Most also aim to cater to beginners, but some also provide valuable information which can be used by experts as well. These are not only free, but are also regularly updated as per the changes in the domain. It also allows discussions with the writer, which can help a learner in getting more clarification. Some of the blogs one can read are:
- Scraping.pro
Founded in 2012 by Michael Shilov, Scraping.pro posts articles about web scraping tools and tutorials along with comparisons and analysis between different scrapers. The blog aims to solve the problems of those people who face difficulties while extracting information from the internet.
- Octoparse.com
This is an official blog belonging to a top free web scraping tool – Octoparse. It covers articles on web scraping tools and tutorials. It also shares new information on web scraping as developments take place, and is an ideal blog to follow for learning tips and tricks of web scraping.
Final Takeaway
Although complicated, web scraping is not difficult once a learner identifies the sources from where he or she wants to learn. One might prefer books over videos and vice versa. But it is advisable to learn from different sources and through various mediums as it provides a different perspective. One can further read about some of the Python Web Scraping Tools that are mostly used by data scientists these days.