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.
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 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.
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.
Pluto.jl is a Julia programming environment designed for learning and teaching, and it is a great way to get started with Julia programming, packages and visualisation. Pluto.jl is easy to install, and you can write interactive documents with no prior experience.
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:
The official website for the Julia Language. Julia is a language that is fast, dynamic, easy to use, and open source. Click here to learn more.
Julia Programming: A Hands-On Tutorial, and Numerical Computing in Julia by Martín D. Maas. Introductory material about Julia, focusing on its use in Science and Engineering. Zero2Hero intensive workshop by George Datseris .
Julia enables package developers and users to document functions, types and other objects easily via a built-in documentation system. The basic syntax is simple: any string appearing just before an object (function, macro, type or instance) will be interpreted as documenting it (these are called docstrings ).
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.
