williambyrd / julia

The Julia Programming Language

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The Julia Language

Julia is a high-level, high-performance dynamic language for technical computing. The main homepage for Julia can be found at julialang.org. This is the GitHub repository of Julia source code, including instructions for compiling and installing Julia, below.

Resources

• Homepage: https://julialang.org
• Binaries: https://julialang.org/downloads/
• Source code: https://github.com/JuliaLang/julia
• Documentation: https://docs.julialang.org
• Packages: https://julialang.org/packages/
• Discussion forum: https://discourse.julialang.org
• Slack: https://julialang.slack.com (get an invite from https://julialang.org/slack/)
• YouTube: https://www.youtube.com/user/JuliaLanguage
• Code coverage: https://coveralls.io/r/JuliaLang/julia

New developers may find the notes in CONTRIBUTING helpful to start contributing to the Julia codebase.

External Resources

• StackOverflow
• Twitter
• Learning resources

Binary Installation

If you would rather not compile the latest Julia from source, platform-specific tarballs with pre-compiled binaries are also available for download. The downloads page also provides details on the different tiers of support for OS and platform combinations.

If everything works correctly, you will see a Julia banner and an interactive prompt into which you can enter expressions for evaluation. You can read about getting started in the manual.

Note: Although some system package managers provide Julia, such installations are neither maintained nor endorsed by the Julia project. They may be outdated, broken and/or unmaintained. We recommend you use the official Julia binaries instead.

Building Julia

First, make sure you have all the required dependencies installed. Then, acquire the source code by cloning the git repository:

git clone https://github.com/JuliaLang/julia.git

By default you will be building the latest unstable version of Julia. However, most users should use the most recent stable version of Julia. You can get this version by changing to the Julia directory and running:

git checkout v1.7.0

Now run make to build the julia executable.

Building Julia requires 2GiB of disk space and approximately 4GiB of virtual memory.

Note: The build process will fail badly if any of the build directory's parent directories have spaces or other shell meta-characters such as $ or : in their names (this is due to a limitation in GNU make).

Once it is built, you can run the julia executable after you enter your julia directory and run

./julia

Your first test of Julia determines whether your build is working properly. From the UNIX/Windows command prompt inside the julia source directory, type make testall. You should see output that lists a series of running tests; if they complete without error, you should be in good shape to start using Julia.

You can read about getting started in the manual.

Detailed build instructions, should they be necessary, are included in the build documentation.

Uninstalling Julia

Julia does not install anything outside the directory it was cloned into. Julia can be completely uninstalled by deleting this directory. Julia packages are installed in ~/.julia by default, and can be uninstalled by deleting ~/.julia.

Source Code Organization

The Julia source code is organized as follows:

Directory	Contents
base/	source code for the Base module (part of Julia's standard library)
stdlib/	source code for other standard library packages
cli/	source for the command line interface/REPL
contrib/	miscellaneous scripts
deps/	external dependencies
doc/src/	source for the user manual
src/	source for Julia language core
test/	test suites
usr/	binaries and shared libraries loaded by Julia's standard libraries

Terminal, Editors and IDEs

The Julia REPL is quite powerful. See the section in the manual on the Julia REPL for more details.

On Windows we highly recommend running Julia in a modern terminal, such as Windows Terminal from the Microsoft Store.

Support for editing Julia is available for many widely used editors: Emacs, Vim, Sublime Text, and many others.

For users who prefer IDEs, we recommend using VS Code with the julia-vscode plugin. For notebook users, Jupyter notebook support is available through the IJulia package, and the Pluto.jl package provides Pluto notebooks.