How Many Languages Should You Program In

I love programming languages. Some would say that I am a language addict. I have programmed in a lot of languages, and written blog posts promoting their use.

What is a reasonable number of languages to program in?

For production code my answer is almost always:

Less is more

There is a tricky balance between innovation and stability in software engineering. This post has a few metrics and some hand-wavy advice on language use.

Too Many Languages

Projects using a lot of languages are the worst. Their lack of discipline makes them hard to understand and maintain. You have a deadline but you keep getting dragged into rabbit holes. Their main benefit is resume building. Often projects with many languages also have:

• Several different NoSQL and SQL databases
• Every web or Microsoft framework that was cool at some point
• Every service on AWS

Return on Investment

A good metric for whether you should add a new language to your project is to look at the ROI, return on investment. Learning a new language is usually pretty easy, but learning the build system and the ecosystem is a lot harder. We have good connectivity from languages to SQL database, but getting more languages working closely together is tedious. You need a strong value proposition to add a new language.

Language Specialization

The best reason to use several languages is that you are forced to use a given language category.

• Statically compiled back-end language
• Scripting language
• Front-end language 
• ML / Numeric language
• Non garbage collected system language

Often the libraries for a given domain are written in one or a few languages. For instance computer vision libraries are written in C++ or Python. Then you are forced to use them.

Redundancy

In scripting languages my preference is Python, but I will happily use Groovy, Perl and Ruby. Using similar scripting languages on the same project feels messy.

Using several languages inside an ecosystem say Java and Scala or C# and F# causes less friction.

Language Tool-belt

I have to be fluent in a few languages for work and I have limited capacity, but once a year I will try out a new language for a while and see if it has staying power. Most of them don't but it keeps my skill set up to date. When my boss asks me to spend a couple of days updating an old throwaway React project I get a running start.

Metrics from A.I. and ML

These two concepts from artificial intelligence are relevant to the adoption of programming languages and evolution of long lived software systems.

• Learning rate
• Multi armed bandit algorithm

Learning rate is how fast you change the weight of your neural network after each training run. If you choose a high value, your neural network jumps erratic and doesn't learn, if the learning rate is too low it moves too slow and doesn't learn. More sophisticated algorithms like Adam start with a high learning rate that gets smaller for a trained system.

Multi armed bandit algorithm is for choosing what stories you should show on the front page of a news site. The gist is that you should show popular stories, but you give a percentage of the space to new stories for a chance to become the popular stories.

I am in the flow when I use 10% of my time learning and 90% working.

To Add or Not to Add

Learning a new language is fun. It teaches you new ways to think.

If you want to add a new language to an established project you should be familiar with both language and ecosystem, and expect a substantial productivity or performance gain before it is worth the overhead.

Otherwise if you want to get serious with a new language do open source work or use it on smaller projects.