Julia for Analysts: Tips for Better Beginnings - Pick the right IDE (#2)


TL;DR

While it might be tempting, resist the urge to use Jupyter Notebooks (/ Jupyter Lab) and use Julia in VS Code (with the Julia extension) instead. If you do only light analyses, consider Pluto.jl. If you need the cloud compute or don't want to install Julia, try JuliaHub.

Pick the Right IDE

Warmup: Julia REPL + Tmux

If you use REPL a lot, look into combining it with tmux (see the previous article (#1)). It will allow you to "hide" your opened Julia REPL session.

It is not a fully-fledged replacement for an IDE, but it can help with a lot of quick tasks. You can use your "hidden" Julia REPL session as a quick-access super-powered calculator / Excel replacement / file scanner.

Try it:

Read more: Quick and Easy Guide to Tmux

Difficulty: Low
Downsides: None (except for the layer of complexity, I would suggest avoiding any window management)

VSCode (+Tmux)

The most modern and popular (seemingly) environment for Julia. It offers a modern IDE and a notebook-like experience if you want to combine both.

You must install the Julia VS Code extension is incredible! Read more here.

🔥🔥🔥 Nowadays, you can start a VS Code server from any remote machine and connect to it via your Github account. It's a similar experience to using VSCode on JuliaHub.

A few things that are worth configuring (Extensions - Julia - Extension Settings):

Other tips:

Difficulty: Low
Downsides: None

(N)Vim + Tmux

This is not for Julia beginners unless you're already familiar with it.

Vim is a highly configurable text editor. The main difference I see is that you operate not with arrow keys or a mouse but by executing "motions" that can perform incredibly complex tasks (and then you can easily repeat them).

It is my personal favourite and it has led to a significant boost in my productivity. But it requires a lot of setting up (a lot lot lot). Once you do, you will need 1-2 weeks to get used to it but then it becomes so enjoyable! It feels like playing a game while working - sometimes I make some changes, undo them and think about the best power combo to achieve the same.

I believe the trick is to combine the best of Vim and modern tools we have, eg, nvim+lua, use your mouse when it's faster, scroll with it (Neoscroll), don't use registers, etc. Basically, do things the way that is the most convenient / the fastest for YOU.

I'd recommend:

Other resources:

Difficulty: High
Downsides: Very steep learning curve. Not suitable to learn at the same time as Julia

IJulia (Jupyter Notebook/Lab)

The standard entry point via the Jupyter Notebook or Jupyter Lab experience. I have learned Python in it and I'm grateful for how easy it was, but Julia REPL + VS Code is much better.

It is still a good option if you're bound to big cloud platforms (eg, AWS Sagemaker Notebooks), but if you can look into VS Code Server. If you need both the compute (big cloud machines) and Julia, JuliaHub is the best option.

A few tips to make the transition easier:

Difficulty: Low
Downsides: Missing many perks of REPL and associated packages (eg, OhMyREPL, REPL special modes, REPL history)

Others

I have listed only the options I have used a lot to have a basis for comparison, but there are many more.

Pluto.jl

Pluto are reactive notebooks (ie, re-evaluating on every "input" change). They are an incredible choice for quick interactive presentations, visualizations, and teaching.

If you have simple analyses (a single file) that don't take long and don't mind working with smaller code blocks (it operates on individual statements to be reactive), Pluto.jl is the best choice for you.

See: Pluto.jl and an amazing resource on building slides with Pluto.jl

JuliaHub

It's strictly not an IDE. It's a cloud service from Julia Computing that allows you to spin up and down Pluto.jl notebooks, VS Code with arbitrary computing power.

If you don't want to install Julia on your computer, JuliaHub is the best choice.

Emacs

I have met as many Julia users using Emacs as those using Neovim, so definitely a popular option. Somehow it tend to be people with Computer Science background.

See: Julia-emacs and julia-snail

CC BY-SA 4.0 Jan Siml. Last modified: August 24, 2022. Website built with Franklin.jl and the Julia programming language. See the Privacy Policy