Julia
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Julia has been downloaded over 45 million times and the Julia community has registered over 10,000 Julia packages for community use. These include various mathematical libraries, data manipulation tools, and packages for general purpose computing.
- Download
Almost everyone should be downloading and using the latest...
- Documentation
It is multi-paradigm, combining features of imperative,...
- Learn
Julia is ready for the classroom. We encourage instructors...
- 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 generally fields a large number of...
- Shop Merchandise
The official website for the Julia Language. Julia is a...
- Download
Almost everyone should be downloading and using the latest stable release of Julia. Great care is taken not to break compatibility with older Julia versions, so older code should continue to work with the latest stable Julia release.
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.
Julia is ready for the classroom. We encourage instructors to participate in the Julia community for questions about Julia or specific packages. This page puts together various resources that instructors and students alike may find useful. See where Julia is being taught today.
The easiest way to learn and experiment with Julia is by starting an interactive session (also known as a read-eval-print loop or "REPL") by double-clicking the Julia executable or running julia from the command line:
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.
Julia is a high-performance, dynamic programming language for modern technical computing. It solves the two language problem by being simultaneously as fast as C and as easy as Python.
