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How to Install Julia Programming Language on Ubuntu 22.04

Published on September 30, 2022
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By Tony Tran
Developer and author at DigitalOcean.
How to Install Julia Programming Language on Ubuntu 22.04


Julia is a programming language designed to be high performance in computation and analysis. It is popular in data science, scientific research, visualization, machine learning, and also for more general purpose application building. The official site provides a live demo for you to try out the Julia language, but for practical use and development you will need to install it onto your system.

This tutorial will cover downloading and installing Julia on your machine. This will include making Julia discoverable to your system, and invoking an interactive REPL session for you to code using Julia.


Step 1 — Downloading and Installing Julia

Pre-compiled binaries are the recommended method of installing Julia, though there is an option to compile Julia from source if your needs require that. In this tutorial you will download the official pre-compiled binaries from Julia’s official download page. Make sure you are in your home directory, then start the download:

  1. wget https://julialang-s3.julialang.org/bin/linux/x64/1.8/julia-1.8.1-linux-x86_64.tar.gz

This command uses wget to download the official pre-compiled binary. To complete the installation, extract the downloaded archive. This is done with the tar command:

  1. tar zxvf julia-1.8.1-linux-x86_64.tar.gz

Julia’s installation is now complete, in a new directory named julia-1.8.1. This location is referred to as your julia directory, and will be referenced later. Julia is entirely contained in this single directory. In the future if you wish to uninstall Julia, you can delete this directory for a complete uninstall.

Step 2 — Adding Julia to your PATH

While installation is complete, your system will need to be able to find the julia executable. This can be done by adding the full path of Julia’s bin directory to the PATH environment variable ~/.bashrc. This is one of the locations Linux allows adjustments to your PATH. Open it using nano or your preferred text editor:

  1. nano ~/.bashrc

Add this line to the bottom of the file, using the julia directory you installed Julia to as the basis:

. . .
export PATH="$PATH:/home/sammy/julia-1.8.1/bin"

You are required to use the absolute path to your bin folder. In this example, the home directory is used, so be sure to update the directory name accordingly if you chose a different location for your julia directory.

Once you are done, save and exit by pressing CTRL+O then CTRL+X.

In order for this change to go into effect, you have to source your .bashrc file:

  1. source ~/.bashrc

Now your system can find the julia executable.

Step 3 — Running the Julia REPL

To confirm Julia is installed correctly and to start experimenting with the language itself, start an interactive REPL (read-evaluate-print-loop) session. This will allow you to get immediate feedback and use the language itself.

With julia now on your PATH, you can start your session with this command:

  1. julia
_ _ _ _(_)_ | Documentation: https://docs.julialang.org (_) | (_) (_) | _ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help. | | | | | | |/ _` | | | | |_| | | | (_| | | Version 1.8.1 (2022-09-06) _/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release |__/ | julia>

As an example and to verify it works, you can start with doing basic arithmetic using Julia, which is a staple for any programming language:

  1. 1 + 1

Once you are done experimenting, you can hit CTRL+D to exit the session.


Julia is a programming language used for data science and application building. While this guide is only covering the installation and basic usage, you can learn more about programming and creating with Julia on the official Julia learning site. If you are interested in installing other languages, especially for data science, check out our tutorials on how to install R.

If you’ve enjoyed this tutorial and our broader community, consider checking out our DigitalOcean products which can also help you achieve your development goals.

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About the authors
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Tony Tran


Developer and author at DigitalOcean.

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