Building a piece of software from scratch is engaging and fun. It’s especially engaging when you want to build something that interacts with web pages and extracts data from them, such as a web scraper. However, as an absolute beginner, you might be confused about whether to run C++, PHP, or Python web scraping operations.

Today we are going to help you find the answer to that ultimate “How to build a web scraper?” question. But before we give you any definitive guidelines, let’s see the definition of web scraping, what it is used for, and where do you start.

How to Build a Web Scraper

The Definition of Web Scraping

Web scraping refers to the process of gathering public data from web pages. Web scraping operations can target specific websites using pre-defined criteria to extract exactly the data you need. The data can be text, images, or both.

Who runs the operation? Web scraping is handled by web scrapers – whether it’s Python web scraping or Ruby web scraping, the goal is the same. Find the target public data on a web page, extract it, and store it in a specific location.

Common Uses of Web Scraping

Why would you build a web scraper to start with? Web scraping is a widely accepted practice, and you can see it across industries. It has numerous use cases. Web scraping can help companies run an ongoing price monitoring strategy to get the data needed for fueling their dynamic pricing decisions.

Web scraping is very useful when it comes to online brand image management. Web scrapers can go through social media platforms, pinpoint the brand mentions, and enable companies to understand why their customers love or hate them. The same applies to consumer forums and reviews. These are perfect for web scraping use, especially if you want to have insight into current customer sentiment.

Marketing professionals use web scraping to identify certain trends, politicians to extract the news to predict election results. The list goes on. If you need to scrape off the data from the world wide web – web scraping is your go-to solution.

How Are Web Scrapers Built?

Unfortunately, scrapers are not like a WordPress site. In other words, you can’t have up and running without writing a single line of code. To build a web scraper, you will need to code it using one of the many available web scraping frameworks, tools, libraries, and programming languages. For instance, there are two Python web scraping frameworks available, PySpider and Scrapy.

How Are Web Scrapers Built

Building a scraper able to extract the entire HTML structure from a web page is easy. You’ll find a lot of examples online no longer than a few lines of code. However, it becomes tricky when you want to extract very specific data found on a page. You shouldn’t worry about it at the moment as you are only a beginner.

Where to start

Where do you start as a beginner? First and foremost, you need to stay on top of HTML structures. You need to know all HTML elements and the web page structure to identify elements and attributes you want your web scraper to scrape.

The HTML element is everything that starts with a tag and ends with the tag. For instance, you will see a lot of <h1>, <h2>, and <p> elements on a page. The most common attributes are class and id. This knowledge can help you code your scraper, so it selects only elements with a specific type and attributes.

Once you know your HTML structures, you are ready to choose a programming language for building a web scraper.

Different Languages for Building A Web Scraper

We’ll leave learning how to code to you. We can help you make an informed decision whether to choose a Python web scrape or Node.JS web scraper, for instance. Here are the most noteworthy pros and cons of every programming language.

Python Web Scraping

Pros

  • Most popularly used language for web scraping
  • Great community with a lot of helpful guides
  • Ready to use libraries and frameworks (BeautifulSoup, Scrapy, Selenium)

Cons

  • Possible slower execution

If you want to learn more about Python web scraping, we suggest reading Oxylabs step-by-step web scraping tutorial for more info.

Node.JS Web Scraping

Pros

  • Easily parse HTML with Node libraries (Jsdom)
  • Support for headless browsers (Puppeteer)
  • Easily target data with selectors (CheerioJS)

Cons

  • Requires substantial knowledge of JavaScript
  • It’s not perfect for large-scale data scraping operations

C++ Web Scraping

Pros

  • Easy to scrape specific data
  • No need to use the library to convert HTML documents into searchable data
  • Great for large-scale scraping operations

Cons

  • It’s not best suited for creating crawlers
  • It requires significant time and effort to build everything from scratch

Ruby web scraping

Pros

  • Great Xpath and CSS selector support (Nokogiri)
  • Easy to build a scraper with HTTPParty and Pry
  • Easily send HTTP requests to multiple pages

Cons

  • Slightly slower than other languages
  • Documentation is hard to find

PHP Web Scraping

Pros

  • It’s easy to code
  • It’s really well supported
  • Writing HTML DOM parser in PHP is straightforward

Cons

  • Weak support for async and multi-threading
  • Queuing and scheduling are major issues

Conclusion

Building a web scraper as an absolute beginner is a challenging but not impossible thing to do. Now you know how the scrapers are built, where to start, and the pros and cons of commonly used programming languages for building web scrapers. If you choose Python web scraping, you’ll find many helpful resources online. But then again, you can build one in any of the above-listed languages.