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1a. Installation and Resources

Martin Alfaro
PhD in Economics

Introduction

In the upcoming sections, we'll cover the essential steps to install and run Julia. Additionally, we'll provide instructions on how to set up VS Code. Its integrated environment will enable you to write and execute Julia code, visualize results, and leverage artificial intelligence tools like GitHub Copilot.

This section in particular focuses on the installation process, while also pointing you to valuable resources to further your knowledge about the language.

Installing Julia

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All the links mentioned on the website are included in Links, located in the left navigation bar.

To download Julia and access its official documentation, visit Julia's official website. Note that the installation process depends on your computer's operating system.

Installing an Editor

Once Julia is installed, you'll need an editor to write scripts and view outputs. There are numerous alternatives in this respect. Our website supposes that you use Visual Studio Code (aka VS Code), which is free, officially supported by Julia, and runs on any operating system (i.e., Windows, macOS, and Linux). One of the key benefits of VS Code also is the possibility of installing plugins to extend the editor's capabilities. In fact, you'll need to add the Julia Language Support plugin for running Julia.

Links to other popular editors can be found on Useful Links, including Vim, Emacs, NotePad, and Sublime. These editors are officially supported by Julia (except Sublime). I strongly recommend getting proficient in either VS Code or one of these alternatives. In this way, you'll be able to master a single tool for coding in multiple programming languages.

Warning!
Avoid getting used to specialized editors built for one particular language, such as RStudio for R (or its newer version Posit). The editors I mentioned were designed for coding, regardless of the programming language you choose. Mastering a general code editor will enhance your coding skills—you'll be able to apply the same tools and keyboard shortcuts to every language you work with.

Installing R and Python (OPTIONAL)

Julia allows for seamless integration with other programming languages, including R and Python. For example, you can export data to R or Python from Julia, perform specific operations, and then import the results back into Julia. This interoperability is particularly useful when a desired function is available in R or Python but not in Julia.

If you're familiar with R and Python, you may find this note helpful. It outlines noteworthy differences between these languages and Julia. Additionally, see the following cheat sheet For a quick reference on the syntax differences in Matlab, Python, and Julia.

Julia's Resources for Help

There are two official resources for learning Julia.

  1. Julia's official documentation. Written by Julia's developers.

  1. Julia Discourse. Official forum to ask questions about Julia.

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