Alternate Programming Languages for Web Scraping

edward robinson 0
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Because of the growing popularity of data extraction, more people have been developing better ways to collect useful market data.

This has seen a rise in alternate web scraping languages. These are new programming languages, such as Golang, outside the usual ones that people are familiar with, such as Python, Node, and C.

These new languages were built largely from the limitations and setbacks commonly associated with the older, more established languages.

In this text, we will consider three of these alternate languages and how they generally affect web scraping, and what unique properties they offer.

An Overview of Web Scraping

Web scraping can be explained as the automated process that web users employ in gathering large quantities of market data from several sources on the web.

Web scraping is now popular for being the most advanced yet simplest way to get data from all over the internet, regardless of where the user resides.

The best thing about web scraping is that if the data is publicly available on the web, it can be scraped quickly and with very few errors.

Several kinds of tools are used for web scraping, and while some can be self-built and hosted, others need to be acquired from a third-party company.

The process through which web scrapers work to extract data is simple and can be explained as shown below:

  • First, the user collects several related URLs from which to harvest the data eventually. This process is carried out using web crawlers
  • The harvested URLs are fed into the scraper, and the request is sent out using a headless or non-headless browser
  • The request is often convened to the destination using proxies to ensure security and efficiency
  • Once the requests reach the targeted servers, the HTML files in raw form are extracted
  • Then the results are returned via the proxy route once again before they are parsed and transformed into structured formats
  • Finally, the extracted data is saved as a structured file such as Excel Spreadsheets, CSV, or JSON files.

The extracted data can be used for many core business operations, such as the following:

Creating Business Insights

Data helps businesses stay afloat and even dominate their respective markets by providing the right information to create the best business insights.

These insights help to control how decisions are taken and since relevant and accurate data back them, they help spur growth.

Developing Strategies

Businesses can also develop working plans and strategies by simply following what the market data says.

These strategies can affect everything from how prices are set to when to manufacture certain products or penetrate certain markets.

Monitoring Competition and Markets

Data also helps brands monitor their rival and the general market. Monitoring competition is another effective way to make certain adjustments or create strategies.

And monitoring the market allows the brand only to create customer-centric products and services.

If nothing else, these help to keep a brand continually successful.

The 3 Alternative Programming Languages

The following are three alternative programming languages that are not yet as popular as the most common ones:

Ruby

Ruby, howbeit very popular, is not as commonly used as other languages such as Python and JavaScript.

Yet, it is a language specifically built for web scraping with powerful libraries that can extract and parse HTML and XML files.

While its lack of common application may come with very little community, Ruby has several benefits.

For instance, it requires fewer lines of code to write a model in Ruby than it does with Python.

It also has a huge GitHub repository which means a user can use and deploy existing packages without doing too much.

Lastly, the Ruby library known as Nokogiri has recorded better success dealing with broken HTML codes than any other language.

Ready-Made Solutions

Another effective yet rarely used web scraping tools are those built and managed by a third-party company.

Most of them are open-sourced, and others are even free for use. This solution also eliminates the need to write too many codes, and writing a few lines of code only becomes necessary when you need to make some modifications and customizations.

The tool may be restrictive, allowing you to do only what the software supports, and it might not support proxy integration, yet it is the quickest way to access publicly available data without doing much.

Golang

This programming language is not as commonly applied because it was only released in 2009 and has not grown enough to have a learning curve.

Because of its newness, there may still be little difficulties when trying to implement and integrate with other platforms.

Golang is also known as Go and is built to be faster and more organized than the older languages.

A tool such as a Golang web scraper would be faster and more efficient than another built with Python. If you’re curious how to build a custom web scraper in Golang yourself, Oxylabs offers a detailed tutorial – check the article they wrote to learn more.

Conclusion

As data continues to grow and web scraping becomes more advanced, people and businesses need more alternatives to extracting data.

The alternatives described above are faster and easier to use than the older languages, especially once you can dedicate some time to learning them.