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JuliaLang julia
The Julia Programming Language
Stars
49,063
Forks
5,982
Watchers: 49,063
Language
License: MIT License
Repository Radar Score
65 / 100
Growth
- 7d
- +0
- 30d
- +0
- %
- 0.0%
Not enough metric snapshots yet to chart growth for this repository.
Score breakdown
- popularity 86
- growth 0
- activity 100
- freshness 100
- community 90
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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.
- Homepage: https://julialang.org
- Install: 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
- Zulip: https://julialang.zulipchat.com/
- 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
We welcome contributions from developers of all experience levels, including bug fixes, documentation improvements, tests, and performance enhancements.
New contributors are encouraged to start by reading CONTRIBUTING.md.
Important
If your pull request contains substantive contributions from a generative AI tool, please disclose so with details, and review all changes before opening. This also applies to other content, such as issues, discussions, and comments.
The recommended way of installing Julia is to use juliaup which will install
the latest stable julia for you and help keep it up to date. It can also let
you install and run different Julia versions simultaneously. Instructions for
this can be found here. If you want to manually
download specific Julia binaries, you can find those on the Manual Downloads
page. The downloads page also provides
details on the different tiers of
support for OS and
platform combinations.
If everything works correctly, you will get a julia program and when you run
it in a terminal or command prompt, 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 OS 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.
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
and then use the command prompt to change into the resulting julia directory. 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 running: (replace [tag] with the desired tag)
git checkout [tag]
To build the julia executable, run make from within the julia directory.
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. From within the julia directory, run
./julia
Your first test of Julia determines whether your build is working
properly. From the julia
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.
By default, Julia does not install anything outside the directory it was cloned
into and ~/.julia. Julia and the vast majority of Julia packages can be
completely uninstalled by deleting these two directories.
The Julia source code is organized as follows:
| Directory | Contents |
|---|---|
base/ |
source code for the Base module (part of Julia's standard library) |
cli/ |
source for the command line interface/REPL |
contrib/ |
miscellaneous scripts |
deps/ |
external dependencies |
doc/src/ |
source for the user manual |
etc/ |
contains startup.jl |
src/ |
source for Julia language core |
stdlib/ |
source code for other standard library packages |
test/ |
test suites |
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.
Languages
Share of the codebase by language, based on repository metadata from the host.
- Julia 68.6%
- C 16.9%
- C++ 9.2%
- Tree-sitter Query 1.6%
- Makefile 1.1%
- LLVM 1.0%
- Rust 0.6%
- Scheme 0.5%
- Shell 0.2%
- Clojure 0.1%
- Objective-C 0.1%
- PHP 0.1%
- Assembly 0.1%
- Inno Setup 0.0%
- Python 0.0%
- Rich Text Format 0.0%
- DTrace 0.0%
- GDB 0.0%
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- High absolute popularity (49,063 stars) signals broad adoption.
- Maintained recently (last push 2 weeks ago).
Who should use it
- Developers working primarily with Julia
- Teams exploring AI tooling, agents, or ML infrastructure
- Platform and DevOps engineers
Potential use cases
- Reference or evaluate Julia open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
- Evaluate automation, CI/CD, or infrastructure patterns
Strengths
- Recent repository activity
- README present in our index
- Declared license: MIT License
- Substantial fork count (5,982) suggests reuse and contribution interest
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Strong signals: Strong community interest · Active maintenance
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.