Web Scraping and Automation

Introduction

Extracting data by navigating through different pages on a website and storing the required data fields is what Web or Data Scraping means. This data can then be used for personal purpose or in an another website that you are to develop. When you need to scrap and extract a large amount of data from the websites continuously you need something called web automation that intern uses different set of codes that perform operations to gather insights. On combining these two concepts we get a very useful concept of automated web scraping that can extract data from multiple pages continuously and store it in a database. There are many tools to achieve this, for example Scrapy, PySpider, Selenium, Beautiful Soup, etc.

There are two main parts in this process: Web Crawler and Web Scraper.

The Web Crawler is an artificial intelligence that browses the internet to specific index and search for content. The Web Scraper is a specialized tool designed to accurately extract data from web pages.

Let us see a few commonly used and easy to learn and implement tools to achieve the above mentioned technique.

Scrapy

Scrapy is an open source framework that has built-in support for extracting the data from HTML web pages. It is programmed in Python and can work on big data set. The biggest advantage of Scrapy is that it is built on Twisted which means it is an asynchronous networking library that allows to move on to another task before the earlier task is completed. This makes the performance more efficient. In terms of JavaScript support it is a little time consuming to inspect and develop the crawler for simulation of ajax/pjax requests. If you are going to need a powerful and flexible web crawler then Scrapy is to be chosen.

Here is how to install Scrapy.

Open a cmd window and type

pip install Scrapy

It will take few minutes to complete the installation.

To store the data that you will scrap , create a new directory and run the following command-

scrapy startproject first_scrapy

This code will create a directory with name firts_scrapy and will contain the following files in it.

Now you are all set to work with Scrapy for your Project. For further reference you can look into the Scrapy Documentation

https://docs.scrapy.org/en/latest/

Beautiful Soup

If you are a beginner, Beautiful Soup is the most preferred one, since it uses a python library for pulling data out of our simple HTML and XML files. It’s easy to install and work with. This tool firstly downloads the web page, extracts the data and saves it locally. This data is can then be analysed according to your requirements. If you are working on low-level complex projects then Beautiful Soup can do your task pretty efficiently and let the code be simple and flexible.

Installing BS4:

Open cmd window and enter:

pip install beautifulsoup4

pip install requests

A sample code to extract data from the page source you need.

The above code loads the page source and extracts the texts by iterating through all review divs.

Beautiful Soup Documentation Website:

https://www.crummy.com/software/BeautifulSoup/bs4/doc/

Further reference:

https://pypi.org/project/beautifulsoup4/

Selenium

Selenium is originally used to automate web browser interaction from Python by providing extensions. It is actually composed of number of tools such as WebDriver, IDE and Grid. It uses minimalist design approach that gives it a benefit to be included as a component in large-scale applications. It is very compatible with the JavaScript codes in your project.This technique is used for browser-based testing to keep up with the possible changes. The setup of this tool is pretty simple and the data is saved in a CVS file which makes he data more understandable. If you are to deal with a JavaScript based web application then Selenium would be a great choice.

Here’s how to install Selenium

Enter the below in cmd window

pip install selenium

You will need to install additional libraries (drivers) when you want to work with Java, Python, C#, Ruby, etc.

For Selenium to work, it must access the browser driver.

Now you are all set to use this for your project.

Selenium Documentation:

https://www.selenium.dev/documentation/en/

Conclusion

Web Scraping becomes interesting to work with when you have a project on the same. You can make lot of productive elements that can reduce the coding in your project by successfully using the tools that favour your specifications.

You can also look for other tools such has Apify SDK, Cheerio, Web scrapper.io, Scraper Chrome Extension and PySpider that can be used for automated web scraping.

Author: Hrutvika Muttepwar