- This topic has 0 replies, 1 voice, and was last updated 9 months ago by Oluwole.
- March 3, 2020 at 3:54 pm #87070Participant@oluwole
The driving force of our digital society is information. Although intangible, information in digital form can exist infinitely – on websites, clouds, local storage devices, and more. Having information, therefore, adds value to you and your organization, the kind of value that can’t always be quantified by money.
Information is power.
We are only able to harness the power of information if we can get access to it and handle it. Since the turn of the century, the internet has grown exponentially in such a manner that there is an entire universe of data now available to us.
This data can be extracted from web pages in some ways, particularly the use of Application Programming Interfaces (APIs). Big companies such as Facebook generally allow users to make use of their APIs at some cost. This ensures that they retain full control of the structure and content of the data being made available to third parties.
For businesses who don’t offer such services, particularly small and medium scale enterprises, getting our hands on information on their websites demands some creativity. Hence the concept of Web Scraping!
What is Web Scraping?
Have you ever copied and pasted information from a website? If your answer is “yes,” then you’ve acted as any web scraper would, albeit on a small and manual scale.
Web scraping is also referred to as Web Data Extraction, Web Harvesting, or Screen Scraping.
Web scraping is a technique employed to retrieve or “scrape” data from a website. The information is collected and stored in a format as desired by the user. It is a form of extracting specific data from the web, usually into a local database or sheet, for later analysis or manipulation.
Although web scraping can be done in a mundane, mind-numbing, manual manner, it is usually referenced as an automated process. It uses intelligent bots to retrieve millions or even billions of data points (such as images, videos, text, product items, etc.) from the World Wide Web.
How does web scraping work?
Web scraping involves two parts – a web crawler and a web scraper. The role of the web crawler is to browse the internet to index and search for content by exploring different links. The web scraper does the job of extracting data quickly and accurately from the web page.
Next, the scraper extracts all of the data on the web page or specific data as preferred by the user. For instance, a user might want all the data on a product page scraped while another user might only need the data on models and prices, neglecting reviews and ratings.
The web scraper will then output all collected data into a format that the user desires. Some common forms include CSV or Excel spreadsheets, and JSON.
Tools for web scraping
There are different approaches one can take towards building a web scraper, ranging from JS tools in jQuery or Node.js to VBA in Microsoft Excel. Python is another useful programming resource whose vast array of libraries and packages make it possible to develop basic web scrapers and test them out live on web pages.
Libraries such as BeautifulSoup provide simple methods and Pythonic idioms for navigating, searching, and modifying web pages. Some other popular tools for web scraping include;
Scraper API – It handles proxies, browsers, and CAPTCHAs, allowing developers to the raw HTML from any website with an API call.
ScrapeSimple – It is a fully managed service that handles custom-made web scrapers for customers. It provides quick response times and is perfect for businesses that want an HTML scraper without having to write any code themselves.
ParseHub – It is simple to use and comes with handy features such as getting data from tables and maps, allowing scraping behind login walls, automatic IP rotation, and going through dropdowns.
Scrapy – Like BeautifulSoup, it is a web scraping library for Python developers. It is fully featured with many middleware modules that integrate various tools that handle cases that make web crawling difficult.
Cheerio – This is for NodeJs developers who want to parse HTML easily. It is swift and provides various methods to extract text, HTML, classes, ids, etc.
Others include Mozenda, Diffbot, Kimura, Goutte and Puppeteer, Webhouse.io, Import.io, ScrapingBee, Scraping-Bot, Dexi Intelligent, ScrapingHub, Apify SDK, Content Grabber, FMiner, Data Streamer, and Outwit.
Why web scrape?
Web scraping serves various interests to businesses and individual users. They can be used in some of these areas;
Price Monitoring – for dynamic pricing and revenue optimization, competitor monitoring, product trend monitoring, and investment decision making.
Alternative Data for Finance – for estimating company fundamentals, public sentiment integrations, and news monitoring.
Sentiment Analysis – for investment decision making, product monitoring, brand and company monitoring, and product development.
News & Content Monitoring – for investment decision making, online public sentiment analysis, competitor monitoring, and political campaigns.
Market Research – for market trend analysis, market pricing, optimizing point of entry, research & development, and competitor monitoring.
Why not web scrape?
Web companies employ a plethora of methods to prevent web scraping, and these usually serve as a deterrent to web scrapers. Some of these methods involve;
- Blocking IP addresses
- High traffic monitoring bots
- Monitoring user-agent strings
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