Julia Compiler
Return to Julia language
- Snippet from Wikipedia: Julia (programming language)
Julia is a high-level, general-purpose dynamic programming language, designed to be fast and productive, for e.g. data science, artificial intelligence, machine learning, modeling and simulation, most commonly used for numerical analysis and computational science.
Distinctive aspects of Julia's design include a type system with parametric polymorphism and the use of multiple dispatch as a core programming paradigm, a default just-in-time (JIT) compiler (with support for ahead-of-time compilation) and an efficient (multi-threaded) garbage collection implementation. Notably Julia does not support classes with encapsulated methods and instead it relies on structs with generic methods/functions not tied to them.
By default, Julia is run similarly to scripting languages, using its runtime, and allows for interactions, but Julia programs/source code can also optionally be sent to users in one ready-to-install/run file, which can be made quickly, not needing anything preinstalled.
Julia programs can reuse libraries from other languages by calling them, e.g. calling C or Rust libraries, and Julia (libraries) can also be called from other languages, e.g. Python and R, and several Julia packages have been made easily available from those languages, in the form of Python and R libraries for corresponding Julia packages. Calling in either direction has been implemented for many languages, not just those and C++.
Julia is supported by programmer tools like IDEs (see below) and by notebooks like Pluto.jl, Jupyter, and since 2025 Google Colab officially supports Julia natively.