- Julia is high performance general purpose programming language built to be fast and dynamic with high level syntax, making it more direct to learn.
- Juila performance benchmarks
- Built around matrix/vectorized computations. For example
[1, 2, 3] * 3 is [3, 6, 9]and
[[1, 2], [3, 4], [5, 6]] * 2 is [2, 4], [6, 8], [10, 12].
- My personal favorite thing in Julia is syntax to define functions. For example typing
f(x) = x + 3creates a function named f that does exactly this process.
- While general purpose, Julia's syntax and paradigms are extremely well suited for mathematics and the sciences.
- Jupyter notebooks are an in-browser interactive coding environment great for projects, curriculum, and everything from rapid prototyping to creating full products. Commonly used with languages like Python and R for data oriented projects, it's fairly direct to configure Jupyter notebooks.
Quickest Setup - Access Julia running in a hosted Jupyter notebook online.
- Create a free tier account on https://juliabox.com/ and get after it :)
Setup and installation of Julia + Jupyter on your own machine (runs faster, loads quicker)
Install the Julia Language on your computer.
Most importantly, add Julia to your $PATH. See https://julialang.org/downloads/platform.html for more detailed information.
For Mac users who use Homebrew to install applications, it's super quick to run
brew cask install julia. This process will also automatically put Julia in your $PATH.
Install Jupyter, the in-browser interactive programming environment.
Open up the Julia REPL by launching the application or running
julia from your terminal.
Once in the Julia repl, type
using Pkg and then run
Pkg.add("IJulia") to install IJulia on your machine.
Launch Jupyter and you'll see the Julia language listed as one of your kernels!