From the website:
Efficient, expressive, elegant – Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula.
A different way of seeing this is: Nim is a compiled language that can be as fast as C, with a syntax that can be as intuitive as Python.
It's a compiled language that can produce fast programs
Sometimes it will be really convenient to distribute a binary rather than a script that will rely on several dependencies
The syntax is Python-like and will look familiar for a lot of bioinformaticians
It already has a niche in web applications (with a framework called Jester)
Good support of metaprogramming, that allows to create domain specific languages
C libraries can be easily wrapped and utilized in Nim programs
There are links to bioinformatics projects in Nim in a separate page.
This document aims at being a gentle but concise introduction to nim for bioinformaticians. The assumptions are:
You already are very familiar with Linux and the command line (macOS terminal is equally supported)
You have some scripting knowledge. Knowing some Python is a very good way of starting your journey to Nim, but any other programming language can do the trick
You know bioinformatic file formats and are familiar with Next Generation Sequencing (that happens to require a lot of high throughput processing of quasi-garbage files)
There are excellent tutorials, so this book focuses on complete minimal examples for each topic presented.
While it's feasible to learn Nim without an extensive knowledge of programming, if you never wrote any kind of program or script I would recommend to start with something different. A good choice for most of the bioinformatics needs is Python.
If you get stuck you are more likely to find a solution to your problem if you adopt a popular programming language (like Python or Perl), and if you need to perform some common tasks (like parsing a GenBank file) you will find robust libraries for Perl and Python, but you are un likely to find a heavily tested and adopted solution for Nim, at the moment.
I think Nim has concrete possibilities to catch up quickly (for example, it's relatively straighforward to "adapt" C/C++ libraries to be used from Nim).
It's also worth remembering that nowaday you probably don't need to program yourself, as there is plenty of bioinformatics packages addressing a wide variety of needs.