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Julia is a dynamic programming language for technical computing that is high-level and high-performance. It solves the two-language dilemma by combining the usability of R and Python with the performance of C and Fortran. Julia has a powerful compiler, distributed parallel processing, numerical precision, and a sizeable mathematical function library. In addition, Juno and Jupyter environments give a robust development environment with interactive visuals.

Libraries supplied by the community are being added at a rapid rate. Julia programs are arranged around multiple dispatches - by creating and overloading functions with various combinations of parameter types. Argument types are user-defined, which contributes to Julia's expressiveness.

The Julia compiler comprises a Scheme (FemtoLisp) parser, certain compiler passes and the runtime in C, code compilation via LLVM using C++, the additional compiler passes (type inference, inlining, and so on), as well as most of the Base library written in Julia. The LLVM compiler framework is used for just-in-time production of 64-bit or 32-bit efficient machine code.

Julia has foreign function interfaces for various programming languages, including C, C++, Python, R, and Java. In addition, Julia's C API allows it to be incorporated into any other software. Many of these interfaces are high-performance and, to the most significant degree, eliminate data duplication.