Julia
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Julia is a fast, dynamic, and general-purpose language that supports multiple platforms and paradigms. Learn about its features, ecosystem, packages, and community resources.
- Download
Almost everyone should be downloading and using the latest...
- Documentation
It is multi-paradigm, combining features of imperative,...
- Learn
The Julia Language's YouTube is the one stop shop for all...
- Blog
The Julia blog discusses issues of numerical, technical,...
- Community
Please take a moment to read the Julia Community Standards....
- Contribute
Welcome to the Julia Ecosystem Contributor’s Guide and to...
- JSoC
The Julia organization is a participant in Google Summer of...
- Diversity
Diversity. As a NumFocus supported project, we abide by...
- Download
Julia is a high-performance, open source programming language for data science, machine learning, and computation. Learn how to download and install the latest stable or upcoming release of Julia for various platforms and architectures.
Feb 14, 2022 · Since those early days, we've gone from strength to strength - participating in NumFocus to cement the open source foundations, growing the Julia Lab at MIT where Julia originated into a research powerhouse, and founding JuliaHub (formerly Julia Computing) to build a sustainable business model.
It is multi-paradigm, combining features of imperative, functional, and object-oriented programming. Julia provides ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general programming.
Introduction. Julia Base contains a range of functions and macros appropriate for performing scientific and numerical computing, but is also as broad as those of many general purpose programming languages. Additional functionality is available from a growing collection of available packages.
Learn how to install, run and use Julia, a high-performance dynamic programming language. Find out the differences from other languages, the interactive session features, and the learning resources.
Julia has built-in support for calling C or Fortran language libraries using the @ccall macro. Additional libraries allow users to work with Python, R, C++, Java, and SQL. Separately-compiled executables option. Julia can be compiled to binary executables with PackageCompiler.jl.
