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Contents
Julia is an open-source high-level, high-performance dynamic programming language designed for technical and scientific computing while also being effective for general-purpose tasks. It is convenient to use for daily work but also runs fast enough to be deployed for high-performance applications. Interesting features include: - Large parts of [Julia's base library](https://github.com/julialang/julia) are written in Julia itself. Understanding and contributing to the Julia core does not require knowledge of another language. - Easy to use interfaces to call libraries written in other languages, such as [C, Fortran](http://docs.julialang.org/en/stable/manual/calling-c-and-fortran-code/) and [Python](https://github.com/JuliaPy/PyCall.jl), directly. - [Multiple dispatch](http://docs.julialang.org/en/stable/manual/methods/#man-methods) - A dynamic, nominative and parametric [type system](http://docs.julialang.org/en/stable/manual/types/). - Homoiconicity: Julia code can be represented in Julia itself, making it a good language to learn about [metaprogramming](http://docs.julialang.org/en/stable/manual/metaprogramming/). The first public release was in 2012. You can find out more about the motivation behind it in the blog post ["Why We Created Julia"](http://julialang.org/blog/2012/02/why-we-created-julia) by the core developers. Despite its young age, Julia is already being used in the real world in a variety of fields, such as but not limited to Finance, Data Science and Scientific Computing. You can find many showcase applications on [juliabloggers.com](http://www.juliabloggers.com/) and a list of publications about the language and its technical computing applications [here](http://julialang.org/publications/).
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156 entries across 156 versions & 1 rubygems