Most people know that I’m a huge fan of the Python programming language – while that isn’t going to change, a recent encounter with some researchers at CSIRO has convinced me that I should pick up Julia for some of the energy modelling and optimisation work that I do.
I’ve known for a while that Julia was a language with a lot of benefits (as fast as a lower-level language but with the productivity benefits of a higher-level language). However, if you understand how to write efficient vectorised code in Python (using NumPy and Pandas), then except for some use-cases, you don’t really get that much of a boost out of switching to Julia.
So what changed my mind? Well, for the past few years, the National Renewable Energy Laboratory (NREL) have been working on a number of amazing open-source energy modelling packages for the Julia programming language. I’ve now updated my electricity modelling resources page with the links to some material about these packages.
Being able to leverage these packages to take my energy modelling to the next level was too much of a temptation to pass up, and it is for that reason I am now exploring the world of Julia.
I’ve included the links to a few of the resources I’ve been using to learn Julia below (and if you find any other good materials, please let me know).
Julia Learning Resources
- Getting Started With Julia Programming Language: With Practical Implementation [Article]
- From zero to Julia! [Article series]
- Julia By Example [Article]
- Julia Tutorial [Video]
- Introductory Tutorial on Julia and JuMP [Video]
- Julia Programming For Nervous Beginners [Video playlist]
- Julia Analysis for Beginners [Video playlist]