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m rc1 coming. Need to update to v1.11.6 (July 9, 2025) Long-term support (LTS) release: v1.10.10 (June 27, 2025) |
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By default, Julia is run similarly to scripting languages, using its runtime, and allows for [[read–eval–print loop|interactions]],<ref name="PackageCompiler.jl" /> 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.<ref name=AppBundler.jl /> <!-- controversial on Talk, page, for now commenting out, may move out of lead: Julia programs can also be (separately) compiled to [[binary executable]]s, even allowing no-source-code distribution, and the executables can get much smaller with Julia 1.12. Such compilation is not needed for speed, though it can decrease constant-factor startup cost, since Julia is also compiled when running interactively, but it can help with hiding source code. Features of the language can be separately compiled, so Julia can be used, for example, with its runtime or without it (which allows for smaller executables and libraries but is limited in capabilities). -->
Julia programs can reuse libraries from other languages (or itself be reused from other); Julia has a special no-boilerplate keyword allowing calling e.g. [[C (programming language)|C]], [[Fortran]] or [[Rust (programming language)|Rust]] libraries, and e.g. PythonCall.jl uses it indirectly for you, and Julia (libraries) can also be called from other languages, e.g. [[Python (programming language)|Python]] and [[R (programming language)|R]], and several Julia packages have been made easily available from those languages, in the form of Python and R [[library (computing)|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, [[Project Jupyter|Jupyter]], and since 2025 [[Google Colab]] officially supports Julia natively.
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