Talking in general, what is the process involved if we want to browse some information on the internet and copy it into a local file, let's say for some presentation. We go to the specific website, copy the desired information and paste it into our local file. Seems pretty easy task, right? Since most websites do not allow users to download or save their data, copying and pasting manually is the one of the best choice to achieve results quickly.
Now, Imagine there is a requirement to train a machine learning algorithm for which we want to fetch a large amount of data, including more than 1000s or millions of records from a website and select only specific information from the page’s source code, ignoring the rest which is not required at the moment? Doing the entire process manually and and in less amount of time seems mind-numbing and time-consuming. In simple words, when the same process is automated using a tool, an app or a browser extension it is called Web Scraping.
Web Scraping is an automated process of extracting required data from specific website using automated software or script. It is a process in which a HTTP request is sent to the server which in turn returns the desired page with information, data is then extracted from the page's source code and parsed as structured data into the desired file or database.
For example: One can use Web Scraping to export a list of products from an e-commerce website including the online price and excluding customer reviews onto an excel spreadsheet.
Web Scraping will automatically load, crawl and extract required data from multiple web pages of a website.
Web scraping can also be done manually which involves using browser’s Developer tools for viewing page’s source code, locating/extracting required data, copying and storing it in the desired format. But, as said, it will be a tedious and time consuming activity.
There are many different ways to perform automated web scraping to obtain data from various websites. Large tech-giants like Google, Facebook, Twitter etc have API’s that can access their data in a structured format, which is a best option. But, there are many websites that don’t have this provision, and in such cases Web Scraping plays a major role to scrape their website data. Web Scrapers can come in many different forms including,
Self-built Scrapers (e.g. Just like anyone can build a website, same way anyone can build their own web scraper. One can build a Scraper using Java/Python and browser automation tools like Selenium WebDriver)
Readymade Scraper API’s (e.g. Scraping Bee, Scraping Ant, Crawler, Scrape Goat etc.)
Browser Extensions - Web scraping extensions have the benefit of being simpler to run and being integrated right into your browser (e.g. Chrome Extensions - Web Scraper, Scraper, Agency, Data Scraper etc.)
Scraping Softwares - Just like any other softwares, scraping softwares can be downloaded and installed on your computer (e.g. import.io)
Cloud-based Web Scraper - Cloud-based web scrapers run on an off-site server which is usually provided by the company that developed the scraper itself. This means that your computer’s resources are freed up while your scraper runs and gathers data.(e.g. Bright Data, Mozenda etc.)
Note: If running a Web scraper locally, it will run on your computer consuming local resources. In case the amount of data to be scraped is large enough, it might demand more CPU or RAM which in turn impact your system’s performance, making it very slow.
How does Web Scraping work?
Automated Web Scraping involves scraping tools like Self-built scrappers built using any programming language or Python Scrapy. The basic steps includes,
The tool/automated script sends HTTP request to the hosting server
The server returns the HTML source code of the targeted web pages
Desired data is parsed and extracted from the page’s source code
Structured data is stored in the required format (CSV files, Excel sheet, JSON or Database).
What is Web Scraping used for?
In today’s era, the most valuable asset of any business is its Data. It is often used for data mining and gathering valuable insights from large websites. Web Scraping is used for a variety of business purposes across multiple industries. Lets see some of them,
Data Collection - Collecting data from multiple websites for market research or analysis.
Training and testing data for Machine Learning Projects - Web Scraping helps you to gather data for testing / training your Machine Learning models.
Monitoring e-commerce prices - Web Scraping can be used by companies to scrap competing products data and see how it impacts their pricing strategies
Real Estate Listing Scraping - Many real estate agents use web scraping to populate their database of available properties for sale or for rent
Lead Generation - Many companies collect contact information, including email addresses and phone numbers about potential customers using web scraping for marketing or business purpose
Stock Data Scraping - Finance and investment research firms use web scraping tools to make decisions and create frameworks because it provides relevant and timely information
Financial Data Aggregation - Aggregating financial data from various banking instuitions into one single website e.g. Mint
Is Web Scraping Legal or Ilegal?
Web Scraping is technically not any kind of illegal process but the decision is based on many factors including but not limited to, How the extracted data is used further? Or Did the data scraping process violate any terms and conditions of the website under consideration? The legality of web scraping also depends on the legislation for data sovereignty in the country/state/city where the scraping takes place. Web scraping may become illegal when non publicly available data becomes extracted and is used as your own without the consent of the owner. Web Scraping is actually not illegal on its own but one should be ethical while doing it.
Web Scraping is a very helpful method. If done in a good way, Web Scraping can help us to make the best use of the web, the biggest example of which is Google Search Engine.
I hope through this article I was able to provide you an overview and usage of Web Scraping. Happy Learning!