The efficiency of web scraping depends mainly on the tool used. The process involves crawling, fetching, searching, parsing, reformation, storage, etc. These sub-functionalities must be executed to perfection for a large pool of web data.
Fulfilling the many needs of web scraping necessitates the right software. Hence, using the right programming language. Several programming languages can be used to create a web scraper. But like every other professional, all you need to know about are the best.
What is web scraping?
Web scrapers are tools developed to help automatically collect organized data from the web, storing them for future analysis. The web extraction process has become so useful to 21st-century businesses, as they are invaluable in price monitoring, news monitoring, price intelligence, lead generation, market research, etc.
The internet is laden with unlimited data, and it’s only right your business focuses on data-driven decision-making.
While web scraping sounds like an illegal activity, it is legal. The average internet user performs web scraping on a smaller scale during daily activities. If you copy and paste information from a site to your text or spreadsheet editor, that’s web scraping.
Hence, since web scraping is standard internet practice, why not do it on a large automated scale for more impact? There are two paths towards achieving this; you can patronize web scraping services or build yours. Most times, the latter option is the best, and we’d look at the reasons.
Why you should build an in-house web scraper
Even though building an in-house web scraping tool can be time and money-consuming, some factors make it a profitable investment in the long run.
- Troubleshooting and maintenance: You can control the quality of service from a third-party provider, but you can stay on your engineer’s neck to get maintenance work done.
- Customization: Business needs change over time. So, if you want to avoid hopping from one service to another, building a web scraper in-house gives your flexibility and opportunities to customize to your current needs.
However, if you’re looking for a ready-to-use solution, check out the Oxylabs’ website.
Top 3 programming languages for building a web scraper
When choosing software to build your web scraper, you must consider some factors. Firstly, the popularity of the language is important. The more popular the language, the better because you get better supporting language resources, frameworks, libraries, etc.
Also, the scalability of the language is important. Even if you run a small business as of now, your target is growth. Hence, ensure that the language is scalable. Also, during development, ensure that the software architecture is scalable.
Ease of coding is also important. While web scraping is an important marketing strategy, you don’t need to try building the tool for it with low-level languages. A language with pre-programmed libraries, familiar logic, in-built resources, flexibility, etc., should be on your list.
Other factors to consider are the operational ability to feed the database, the effectiveness of crawling, ease of maintenance, etc. Here are the best programming languages to develop your web scraper in-house.
Python
Most web scraping tools are built with Python because it easily handles all the processes involved in web scraping. Python seamlessly performs the functions thanks to its libraries – Scrapy and Beautiful Soup.
Python is also great with encoding navigation, searches, and modifying a parse tree. The object-oriented programming language is also easy to use. For instance, you can directly use a variable when required.
The excellence of Python in building web scraping also comes through in the ability of a few lines of code to perform major tasks.
Pros:
- It has many libraries.
- It is easy to use.
Cons:
- It’s a general purpose language.
- It’s not the fastest executor.
Node.js
Node.js uses dynamic coding and also supports distributed crawling. As a JavaScript server-side runtime environment, the language events circle to create non-blocking Input/Output applications. Hence, making it easy for users to run several instances of one script. Node.js also has in-built libraries like Express, Request, Request-promise, and Cheerio.
Though you must be an experienced coder to use this language, implementing a working application makes it easier to work with APIs. You also get to work on streaming and socket-based implementations.
Pros:
- Offers fast performance.
- Has quite a number of libraries.
Cons:
- Requires sound programming knowledge
Ruby
The open-source programming language comes with incredible simplicity and functionality. The syntax and style of coding in Ruby make it easy for non-coders to follow along.
Ruby as a language supports both imperative and functional programming. Furthermore, like Python, large tasks can be executed by small blocks of code. The language has a feature called Nokogiiri, which makes it easier to work with broken HTML.
Other commonly used Ruby extensions are Loofah, web scraping with Ruby, and Sanitize.
As a web scraper development language, Ruby edges Python in cloud development. Ruby is also better in terms of deployment. The advantage of Ruby over Python is thanks to the Ruby Bundler system, which facilitates easy package management and deployment from Github.
Pros:
- You can do much with less code on Ruby.
- It has the Nokogiri library that works best for broken HTML code
Cons:
- Has a lean community
- Some new technologies can’t be coded yet with Ruby.
Conclusion
Other popular programming languages you can use to develop web scrapers are C++, Java, and PHP. Whichever of these languages you choose, ensure its strengths help you achieve your business goals.
