Julia is a high-level, high-performance, dynamic programming language. While it is a general-purpose language and can be used to write any application, many of its features are well suited for numerical analysis and computational science.
Distinctive aspects of Julia’s design include a type system with parametric polymorphism in a dynamic programming language; with multiple dispatch as its core programming paradigm. Julia supports concurrent, (composable) parallel and distributed computing (with or without using MPI or the built-in corresponding[clarification needed] to “OpenMP-style” threads), and direct calling of C and Fortran libraries without glue code. Julia uses a just-in-time (JIT) compiler that is referred to as “just-ahead-of-time” (JAOT) in the Julia community, as Julia compiles all code (by default) to machine code before running it.
Julia is garbage-collected, uses eager evaluation, and includes efficient libraries for floating-point calculations, linear algebra, random number generation, and regular expression matching. Many libraries are available, including some (e.g., for fast Fourier transforms) that were previously bundled with Julia and are now separate.
Several development tools support coding in Julia, such as integrated development environments (e.g. Microsoft’s Visual Studio Code, with extensions available adding Julia support to IDEs, e.g. providing debugging and linting support); with integrated tools, e.g. a profiler (and flame graph support available for the built-in one), debugger, and the Rebugger.jl package “supports repeated-execution debugging” and more.