Is a Functional Language the Future of Data Science Scripts?

A functional language is a programming language that is based on the functional paradigm of coding, whereby every process of a program is a function. This allows for greater speed and mitigates the risk of bugs since it's much easier to figure out what's happening in a program as everything in it is modular. In the case of such a program, each module corresponds to a function, having its own variable space. Naturally, this helps conserve memory and make any methods developed this way more scalable.

Functional languages are very important nowadays as people are realizing that their advantages make them ideal in many performance-critical cases. Also, in cases where development speed is a factor, functional languages are preferred. It's important to remember though that many people still favor object-oriented programming (OOP) languages so the latter aren't going to go away any time soon. That's why there are lots of hybrid languages that combine elements of OOP and functional programming.

So far there have been a couple of functional languages that are relevant in data science projects. Namely, there is Scala (where Spark was developed on) and Julia, with the latter gaining popularity as more and more data science packages become available in it. Interestingly, ever since these languages have been shown to provide a performance edge (just like any other functional language), their value in data science has been undeniable, even if many data scientists prefer to use more traditional languages, such as Python.

What about the future of functional programming? Well, it seems quite promising, especially considering how many new programming languages of this paradigm exist nowadays. Also, the fact that there are new ones coming about goes to show that this way of programming is here to stay. Also, since the OOP paradigm has its advantages, it seems quite likely that newer functional languages are bound to be hybrid, to lure more practitioners who are already accustomed (and to some extent vested) in the OOP way of programming. Moreover, functional languages are bound to become more specialized since there are enough of them now to need a niche in order to stand out. In fact, some of them, as for example Julia, appear to have done just that.

If you wish to learn more about the Julia functional language and its application on data science, I have authored two books about it through the Technics Publications publishing house. Feel free to check them out here and learn more about this fascinating functional language. Cheers!