The history of web scraping is very long; In 1989 the World Wide Web(WWW) was launched and after some years World Wide Web Wanderer: The first Perl based web robot was created by Matthew Gray at MIT, the purpose of this web crawler is to measure the size of the World Wide Web. While the wanderer was the first web robot it was not actually been used in data scraping tasks because in 90’s we don’t have an abundance of information(data) but with time as the internet user grows and a wave of digitization came, Web scraping became more and more popular.
We have covered many articles on web scraping and today we are going to discuss all the different web scraping tools, frameworks, and languages.
Let’s answer some of the most asked questions and doubts about web scraping and then we will begin with all the different tools and frameworks for web scraping as we already discussed the short definition and history of web scraping let’s move forward with Q&A.
How different industries use Web Scraping?
Web Scraping became a major part of the E-commerce, Travel, and Recruitment industries. Retail and E-commerce industries make all the marketing strategies, service offering, campaign, and customer services based on data available to them. The E-commerce industry uses web scraping to extract the data and use it to analyze their customer behaviour, sentiments, likes, and recommendations.
Travel industries use web scraping to gather information like hotel reviews, prices, and analytics. Many travels, tourism, and hospitality industries use this data to build business intelligence.
Recruitment agencies do the same as the number of job seekers is increasing so it’s hard to manually pick resumes and find specific skill set candidates, so Web scraping comes very handy for recruiters to pick the best guy according to requirements and job descriptions.
Can a non-programmer do web scraping?
Yes, we have done a couple of tutorials on web scraping where we discussed a non-coder approach to web scrapings like parsehub and Diffbot both provides a Graphical User Interface(GUI) and great documentation of usage guidelines for data extraction they are very easy to use and you can see the processing and outputs in realtime as the utility run.
Web scraping frameworks/software:
Selenium
Selenium was originally developed by Jason Huggins in 2004 as an internal tool at ThoughtWorks(a global software consultancy firm). In Earlier days, It was mostly used for testing, but now it’s widely used for browser automation platforms and, of course, web scraping!
- Selenium is widely used with python language and it is one of the earliest and popular web scraping tools.
- It works with a chrome web browser.
- Can operate web browsers in headless mode(opts.headless =True).
- Selenium provides some of the easy and handy functions for finding elements by name, XPath, tag_name, css_selector, class_name, and partial_link_text.
BeautifulSoup
Beautiful Soup is a Python library that is used for web scraping purposes to pull the data out of HTML and XML files. It creates a parse tree from source code that can be used to structure data in a hierarchical and more readable manner
BeautifulSoup can work with your favourite web parser to provide the best way to search, navigate, and modify the parse tree. Some of the features of BeautifulSoup are as follows:
- Extremely lenient
- Parse pages the same way as a browser does.
- Can Style the Source code in hierarchical tree manner for easy understanding.
- Very fast.
- Support HTML and LXML parser.
- Can easily integrate with other frameworks as we used BeautifulSoup in many articles with urllib, selenium, and request module.
- Contains many inbuilt functions for filtering, structuring, searching, and many more.
- It comes with the most widely used programming languages i.e. Python.
See implementation here
UrlLib & Request
URllib is a python package that combines several modules to preprocess the URLs, in other words, it is a library used for HTTP requests using python language on URLs,
now Urllib is used first before start scraping data from website using any module like selenium, BeautifulSoup, or mechanical soup. Selenium and other libraries don’t have any feature to request data from URL so we use request and Urllib for requesting data.
some of the features of UrlLib library are as follows:
- Supports thread-safe connection.
- Connection pooling.
- Client-side verification using SSL/TLS verification.
- Multiple encoding support.
- Support for gzip and brotli encoding
- Easy method call like urllib.request() for open and read URL and urllib.error() for catching exception raised by urllib.request.
Request is another open-source python library that makes HTTP request more humans friendly and simple to use than urllib as it is made on top of urllib library, it was developed around February 2011.
Some of the features of the Request library are as follows:
- Support fully restful API, and it is easier to use and access.
- Provide POST/ GET functionality on URLs.
- It is used for Web API request purposes.
- Authentication module support.
- Handles cookies and sessions very firmly.
- Provide JSON decoder and Thread safety.
- Multiple files upload.
- Unicode response body.
- .netrc support and SSL verification
- International domains and URLs access capabilities.
Read more about Implementation
MechanicalSoup
It is a python library used to simulate human behavior on web pages. It is made on top of a web parsing library BeautifulSoup. And it is also widely used for web scraping tasks when the websites are having multiple pages and many other elements like popups or timer.
Some of the features of MechanicalSoup are as follows:
- Ability to mimic human behaviour like waiting for a certain event or click items to scrape further hyperlinks.
- Clean library with less overhead code.
- Very fast and automatically follows redirects.
- Support for CSS & Xpath slectors.
- Stores cookies.
- Made on top of Requests, Mechanize, and BeautifulSoup module.
- Can be used for the Browsing interface.
- Interact with websites that don’t provide API.
Puppeteer
Enough about Python-based Web scraping tools, Let’s talk about Puppeteer.
Puppeteer is a Nodejs library used to provide high-level API to control Chrome-like browser and it is used widely by nodejs enthusiasts for web scraping tasks.
Node.js is an open-source server runtime environment that runs on various operating systems like macOS, Linux, Windows, etc. It’s not a programming language, it uses javascript as its main programming interface.
Some of the features of Puppeteer is as follows:
- Nodejs library.
- Control Chromiumusing DevTools Protocol.
- Can Run in both headless and non-headless mode.
- Can create PDF from web pages.
- Provides inbuilt methods for taking screenshots of websites.
- Can create a server-side rendered version of the application.
- Able to Tracks the web page loading process.
- Automate form submission
- Realtime visually surfing the website.
- Can work in websites built with angular and react.
Learn more about the implementation here
Cheerio
We have another Node.Js based Web scraping tool that is specifically designed for web scraping tasks as the Puppeteer is not that fast and also used for automation most of the time.
Cheerio help in interpreting and analyzing the web pages using jQuery-like syntax. It is fast and flexible in comparison to puppeteer and there are many features that make it a more scraping friendly tool like:
- It works on consistent DOM model architecture.
- Very fast in comparison to other node.js based web scraping tools like puppeteer.
- Minimalist function for web scraping.
- Can integrate with other modules very easily.
- Parse markup and provide API for manipulating the data structure.
- Familiar syntax.
- USed @FB55; forgiving htmlparser.
Goutte
We have already seen scraping data using python and node.js but is it possible to scrape data using PHP? The answer is yes due to the abundance of data the research in web scraping techniques is increasing and today we have a variety of web scraping tools based on different programming languages.
Goutte is a PHP based web scraping tool that was originally developed by Fabien Potencier, Who is better known as the creator of Symfony framework, Goutte is based on PHP 5.5+ version and Guzzle 6+(an HTTP client i.e. a requirement of Goutte framework)
Some of the features of using Goutte for your web scraping work are as follows:
- Provide decent API to crawl through websites.
- It extracts data from HTML/XML documents so the source code has to be downloaded before serving it to Goutte.
- Login websites.
- Support POST means you can submit forms using Goutte and extract specific details according to passed attributes.
- Also, run offline on your local computer.
Scraping Bee
Is there any tool that supports multiple languages, almost all programming languages for web scraping?
Yes, we have one tool that is easy to use and supports almost all programming languages like python, ruby, java, PHP, nodejs, and many more. We are talking about ScrapingBee a multi-language based Web Scraping API that was created by Kevin Sahin and Pierre Dewulf, some of the astonishing features of Scraping Bee are as follows:
- Easy Browser surfing in headless mode.
- Dynamic IP(internet protocol) changing for never getting blocked from web sites.
- Scrape web pages in HTML format.
- Used widely for price monitoring.
- It can extract data without getting blocked
- Can throw thousand of requests to the same websites in minutes.
- No rate limit barrier due to dynamic proxies.
- Lead generation directly to Google Sheets.
- Use a large proxy pool.
Parsehub
Yes, a great issue with web scraping was that data is needed by every domain even if its HR, recruitment agency, consultancy firms, Managers, Decision analyst, CEO or any other person who is not into a technical domain that much, but now he/she can also scrape data using GUI (graphical user interface) software like ParseHub.
Parsehub is a visual-based tool for web scraping for non-technical domain professionals, which enables everyone to create their own data extraction workflows without worrying about coding.
A video demonstration of how easy it is to use parsehub interface without coding
Some of the features of ParseHub are as follows:
- A graphical user interfaces with an inbuilt web browser.
- Support export in various formats like JSON, CSV, and Excel.
- Relative Select and click function for web scraping.
- Automatically detects related elements from web pages.
- Real-time time visual web scraping.
- Provides a scraping workflow that shows all the attributes and a real-time result panel for extracting data.
Diffbot
Diffbot is another web scraping tool and it is the most advance of all the GUI-based web scraping tools because it supports machine learning and computer vision that makes the scraping process very fast and handy.
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Diffbot was created by Mike Tung in 2008 at Stanford University. It was the first company to leverage AI for scraping tasks and it comes out very well today Diffbot is been used by top fortune companies on a daily basis. Now according to an MIT Technology Review report as well.
Diffbot is working on the new state of the art AI techniques like GPT-3, but with a different approach, they are trying to vacuuming up a large amount of human-written text data and extracting facts from it instead of training a model directly out of it.
It has multiple features and almost contains every feature for web scraping task as follows:
- Provide an Analyze API to start with when you have no idea with the type of URL.
- Provide Article API to extract information about blogs, articles, and other written text.
- Product API for extracting products just by inserting name and it will return the product color, brand, price, discount, review, and many more features.
- Image API to extract images
- Custom API for creating your own kind of API for your specific web scraping task.
- Knowledge Graph a most talked about feature of Diffbot, it is an intelligence unit that can scrape the whole internet in minutes and gives you corresponding output.
Conclusion
As you might have noticed, they all are either based on some programming languages like python, java, node.js, ruby, PHP, or GUI, but still, a handful of technical expertise is a must if you want to scrape a good amount of data from the internet or you can always opt for GUI tools for web scraping tasks. Above discussed software and modules are free to use and download and some of them provide monthly trials but that is enough to get started with web scraping.
