Download and install Julia on various Operating Systems

Current Release

v0.2.1

Windows Self-Extracting Archive (.exe) 32-bit 64-bit
Mac OS X Package (.dmg) 10.6 64-bit 10.7+ 64-bit
Ubuntu packages 32/64-bit
Source GitHub

Prerelease snapshot

This is a nightly snapshot of the latest version of Julia under development, which you can use to get a preview of the latest work on Julia. However, because Julia is under heavy development, you may be unlucky and get a snapshot with a serious bug, or one which breaks existing packages. Most users are advised to use the latest official release version of Julia, above.

v0.3.0-prerelease

Windows Self-Extracting Archive (.exe) 32-bit 64-bit
Mac OS X Package (.dmg) 10.6 64-bit 10.7+ 64-bit
Ubuntu packages 32/64-bit
Source GitHub

Older Releases

v0.1.2

Windows Archive (.zip) 32-bit 64-bit (Unavailable)
Mac OS X Package (.dmg) 32-bit (Unavailable) 64-bit
Source GitHub Tarball

If the provided download files do not work for you, please file an issue. It is strongly recommended that you download the v0.2 binaries to try out Julia, unless you are working with code that was developed specifically for the v0.1 release.


Platform Specific Instructions

Windows

Julia is available for both 32-bit and 64-bit Windows since XP SP2.

  1. Download the Windows julia.exe installer for your platform. 32-bit julia works on both x86 and x86_64. 64-bit julia will only run on 64-bit Windows (x86_64).
  2. Run the downloaded program to extract julia
  3. Double-click julia.bat in the unpacked folder to start julia

The Windows README contains information on dependencies.

Uninstallation is performed by deleting the extracted directory and the packages directory in %HOME%/.julia. If you would also like to remove your preferences files, remove %HOME%/.juliarc.jl and %HOME%/.julia_history.

OS X

On Mac, a Julia-version.dmg file is provided, which contains Julia.app. Installation is the same as any other Mac software – copy the Julia.app to your hard-drive (anywhere) or run from the disk image. There are separate binaries for Snow Leopard (OSX 10.6) and Lion and above (OSX 10.7+)

Uninstall Julia by deleting Julia.app and the packages directory in ~/.julia. Multiple Julia.app binaries can co-exist without interfering with each other. If you would also like to remove your preferences files, remove ~/.juliarc.jl.

Linux

Instructions will be added here as more linux distributions start including julia. If your Linux distribution is not listed here, you should still be able to run julia by building from source. See the Julia README for more detailed information.

Ubuntu

A PPA (Personal Package Archive) is provided for Ubuntu systems to allow for automatic updating to the latest stable version of Julia. To use this PPA and install julia on Ubuntu 12.04 or later, run the following commands:

sudo add-apt-repository ppa:staticfloat/juliareleases
sudo add-apt-repository ppa:staticfloat/julia-deps
sudo apt-get update
sudo apt-get install julia

Note that Ubuntu has deadlines for accepting new versions of software into their default repositories, and as such the default repositories often have Julia versions that lag behind significantly. When reporting issues, please ensure you are using the latest available release by using one of the PPA repositories displayed on this page.

Uninstallation is platform dependent. If you installed from a package manager such as apt-get, use the package manager to remove julia, for example apt-get remove julia. If you did a source build, you can remove it by deleting your julia source folder. If you would also like to remove your preferences files, they are ~/.julia and ~/.juliarc.jl.

Nightlies installation instructions

A PPA (Personal Package Archive) is provided for Ubuntu systems to allow for automatic updating to the latest beta version of Julia. To use this PPA and install julia on Ubuntu 12.04 or later, run the following commands:

sudo add-apt-repository ppa:staticfloat/julianightlies
sudo add-apt-repository ppa:staticfloat/julia-deps
sudo apt-get update
sudo apt-get install julia

New builds are built every night. If you have already installed julia and you want to upgrade to the latest version, do:

sudo apt-get update
sudo apt-get upgrade

Graphics in Julia

Graphics in Julia are available through external packages. These packages are under heavy development and take different approaches towards graphics and plotting, which suit different use cases.

Winston

Winston provides 2D plotting capabilities for Julia. Add the Winston package to your Julia installation with the following command on the Julia prompt:

  1. Pkg.add("Winston")
  2. using Winston
  3. plot( cumsum(randn(1000)) ) # (plot a random walk)

Winston’s interface will be familiar to MATLAB users. See examples and documentation on the Winston homepage.

Gadfly

Gadfly is an implementation of a Wickham-Wilkinson style grammar of graphics in Julia. Add the Gadfly package to your Julia installation with the following command on the Julia prompt:

  1. Pkg.add("Gadfly")
  2. using Gadfly
  3. draw(SVG("output.svg", 6inch, 3inch), plot([sin, cos], 0, 25)) #(plot a pair of simple functions over a range)

Gadfly’s interface will be familiar to users of R’s ggplot2 package. See examples and documentation on the Gadfly homepage.

Gaston

Gaston provides an interface to gnuplot. Gaston also includes detailed documentation and examples in its manual. Add the Gaston package to your Julia installation with the following commond on the Julia prompt:

  1. Pkg.add("Gaston")
  2. using Gaston
  3. Gaston.set_terminal("aqua") #(this may be necessary, if the following reports that your terminal type is unknown)
  4. x=-pi:.001:pi; y=x.*sin(10./x); plot(x,y) #(plot x*sin(10/x))

In order to use Gaston, you will need to install gnuplot and ensure it is accessible

PyPlot

PyPlot uses the Julia PyCall package to call Python’s matplotlib directly from Julia with little or no overhead (arrays are passed without making a copy). Installation and example usage:

  1. Pkg.add("PyPlot")
  2. using PyPlot
  3. x = linspace(0,2*pi,1000); y = sin(3*x + 4*cos(2*x))
  4. plot(x, y, color="red", linewidth=2.0, linestyle="--")