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}}</ref>
| latest_release_version = {{wikidata|property|edit|reference|Q28974961 |P548=Q2804309|P348}}
| latest_release_date = {{nowrap|{{start date and age|{{wikidata|qualifier| Q28974961 |P348|P577}}|df=y}}}}<br /> and 1.10.
| latest preview version = 1.12.0-
| latest_preview_date = {{start date and age|2025|
| typing = [[Dynamic programming language|Dynamic]],<ref name="Engheim">{{Cite web|last=Engheim|first=Erik|date=2017-11-17|title=Dynamically Typed Languages Are Not What You Think|url=https://erik-engheim.medium.com/dynamically-typed-languages-are-not-what-you-think-ac8d1392b803|access-date=2021-01-27|website=Medium|language=en|archive-date=5 March 2021|archive-url=https://web.archive.org/web/20210305194133/https://erik-engheim.medium.com/dynamically-typed-languages-are-not-what-you-think-ac8d1392b803|url-status=live}}</ref> [[type inference|inferred]], [[optional typing|optional]], [[nominal type system|nominative]], [[parametric polymorphism|parametric]], [[strong and weak typing|strong]]<ref name="Engheim" />
| implementations =
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}}
'''Julia''' is a [[dynamic programming language|dynamic]] [[general-purpose programming language|general-purpose]] [[programming language]]. As a [[high-level programming language|high-level]] language, distinctive aspects of Julia's design include a type system with [[parametric polymorphism]], the use of [[multiple dispatch]] as a core [[programming paradigm]], [[just-in-time compilation|just-in-time]] (JIT) compilation and a parallel [[tracing garbage collection|garbage collection]] implementation. Notably Julia does not support [[Class (computer programming)|classes]] with [[Encapsulation (computer programming)|encapsulated]] methods but instead relies on the types of all of a function's arguments to determine which method will be called.
| date = 15 October 2012▼
| last = Bryant▼
| first = Avi▼
| archive-date= 2014-04-26▼
| title = New Julia language seeks to be the C for scientists▼
| url = https://www.infoworld.com/article/2616709/new-julia-language-seeks-to-be-the-c-for-scientists.html▼
| magazine = InfoWorld▼
| access-date = 4 July 2021▼
| archive-url = https://web.archive.org/web/20140913234252/http://www.infoworld.com/d/application-development/new-julia-language-seeks-be-the-c-scientists-190818▼
| url-status = live▼
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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==History==
Work on Julia began in 2009, when [[Jeff Bezanson (programmer)|Jeff Bezanson]], [[Stefan Karpinski]], [[Viral B. Shah]], and [[Alan Edelman]] set out to create a free language that was both high-level and fast. On 14 February 2012, the team launched a website with a blog post explaining the language's mission.<ref name="announcement" /> In an interview with ''[[InfoWorld]]'' in April 2012, Karpinski said of the name "Julia": "There's no good reason, really. It just seemed like a pretty name."<ref name="infoworld"
▲ | title = New Julia language seeks to be the C for scientists
▲ | url = https://www.infoworld.com/article/2616709/new-julia-language-seeks-to-be-the-c-for-scientists.html
▲ | magazine = InfoWorld
▲ | access-date = 4 July 2021
▲ | archive-url = https://web.archive.org/web/20140913234252/http://www.infoworld.com/d/application-development/new-julia-language-seeks-be-the-c-scientists-190818
▲ | url-status = live
}}</ref> Bezanson said he chose the name on the recommendation of a friend,<ref>{{Cite web |last1=Torre |first1=Charles |title=Stefan Karpinski and Jeff Bezanson on Julia |url=https://channel9.msdn.com/Blogs/Charles/Stefan-Karpinski-and-Jeff-Bezanson-Julia-Programming-Language |website=Channel 9 |publisher=MSDN |access-date=4 December 2018 |archive-date=4 December 2018 |archive-url=https://web.archive.org/web/20181204102053/https://channel9.msdn.com/Blogs/Charles/Stefan-Karpinski-and-Jeff-Bezanson-Julia-Programming-Language |url-status=live }}</ref> then years later wrote:
{{blockquote|Maybe julia stands for "[[Jeff Bezanson (programmer)|Jeff]]'s [[MLisp|uncommon lisp]] is automated"?<ref>{{Cite web |last1=Bezanson |first1=Jeff |title=CAS Benchmarks |url=https://discourse.julialang.org/t/cas-benchmarks-symbolics-jl-and-maxima/58359/17 |website=discourse.julialang.org |date=2 April 2021 |access-date=2 April 2021 |archive-date=2 April 2021 |archive-url=https://web.archive.org/web/20210402224346/https://discourse.julialang.org/t/cas-benchmarks-symbolics-jl-and-maxima/58359/17 |url-status=live }}</ref>}}
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-->
Julia 1.11 was released on 7 October 2024 (and 1.11.
<!-- I think this is now outdated: Some users may want to postpone upgrading to 1.11 (e.g. those calling Julia from R), because of known temporary package incompatibility.
-->
===JuliaCon===
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* Extensible conversions and promotions for numeric and other types
Multiple dispatch (also termed [[multimethod]]s in Lisp) is a [[generalization]] of [[single dispatch]]{{snd}} the [[polymorphism (computer science)|polymorphic mechanism]] used in common [[object-oriented programming]] (OOP) languages, such as [[Python (programming language)|Python]], [[C++]], [[Java (programming language)|Java]], [[JavaScript]], and [[Smalltalk]]{{snd}} that
In Julia, all concrete types are [[subtyping|subtypes]] of abstract types, directly or indirectly subtypes of the <code>Any</code> type, which is the top of the type hierarchy. Concrete types By default, the Julia runtime must be pre-installed as user-provided source code is run. Alternatively, Julia (GUI) apps can be quickly bundled up into a single file with ''AppBundler.jl''<ref name=AppBundler.jl>{{Cite web |title=AppBundler.jl |date=2023-12-13 |url=https://github.com/PeaceFounder/AppBundler.jl |access-date=2023-12-18 |publisher=PeaceFounder |archive-date=18 December 2023 |archive-url=https://web.archive.org/web/20231218172216/https://github.com/PeaceFounder/AppBundler.jl |url-status=live }}</ref> for "building Julia GUI applications in modern desktop application installer formats. It uses Snap for Linux, [[.msix|MSIX]] for Windows, and DMG for MacOS as targets. It bundles full Julia within the app".<ref>{{Cite web |date=2023-11-30 |title=[ANN] AppBundler.jl - Bundle Your Julia GUI Application |url=https://discourse.julialang.org/t/ann-appbundler-jl-bundle-your-julia-gui-application/106971 |access-date=2023-12-18 |website=Julia Programming Language |language=en |archive-date=4 September 2024 |archive-url=https://web.archive.org/web/20240904035046/https://discourse.julialang.org/t/ann-appbundler-jl-bundle-your-julia-gui-application/106971 |url-status=live }}</ref> ''PackageCompiler.jl'' can build standalone [[executable]]s that need no Julia source code to run.<ref name="PackageCompiler.jl">{{Cite web|title=GitHub - JuliaLang/PackageCompiler.jl: Compile your Julia Package.|date=2019-02-14|url=https://github.com/JuliaLang/PackageCompiler.jl|publisher=The Julia Language|access-date=2019-02-15|archive-date=23 March 2019|archive-url=https://web.archive.org/web/20190323182857/https://github.com/JuliaLang/PackageCompiler.jl|url-status=live}}</ref>
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</syntaxhighlight>
Julia uses [[UTF-8]] and [[LaTeX]] codes, allowing it to support common math symbols for many operators, such as ∈ for the <code>in</code> operator, typable with <code>\in</code> then pressing {{keypress|TAB}} (i.e. uses [[LaTeX]] codes, or also possible by simply copy-pasting, e.g. {{not a typo|√ and ∛}} possible for [[square root|sqrt]] and [[cube root|cbrt]] functions). Julia has support for [[Unicode]] 15.1 (Julia 1.12.0-
Julia is supported by ''[[Project Jupyter|Jupyter]]'', an online interactive "notebooks" environment,<ref>{{Cite web |url=https://jupyter.org/ |title=Project Jupyter |access-date=19 August 2015 |archive-date=29 June 2017 |archive-url=https://web.archive.org/web/20170629054445/https://jupyter.org/ |url-status=live }}</ref> and ''[https://github.com/fonsp/Pluto.jl Pluto.jl]'', a "reactive notebook" (where notebooks are saved as pure Julia files), a possible replacement for the former kind.<ref>{{Cite web|last=Boudreau|first=Emmett|date=2020-10-16|title=Could Pluto Be A Real Jupyter Replacement?|url=https://towardsdatascience.com/could-pluto-be-a-real-jupyter-replacement-6574bfb40cc6|access-date=2020-12-08|website=Medium|language=en|archive-date=12 April 2023|archive-url=https://web.archive.org/web/20230412112240/https://towardsdatascience.com/could-pluto-be-a-real-jupyter-replacement-6574bfb40cc6|url-status=live}}</ref> In addition Posit's (formerly [[RStudio]] Inc's) Quarto publishing system supports Julia, Python, R and Observable [[JavaScript]] (those languages have official support by the company, and can even be weaved together in the same notebook document, more languages are unofficially supported).<ref>{{Cite web |last=Machlis |first=Sharon |date=2022-07-27 |title=RStudio changes name to Posit, expands focus to include Python and VS Code |url=https://www.infoworld.com/article/3668252/rstudio-changes-name-to-posit-expands-focus-to-include-python-and-vs-code.html |access-date=2023-01-18 |website=InfoWorld |language=en}}</ref><ref>{{Cite web |date=2022-07-20 |title=Heads up! Quarto is here to stay. Immediately combine R & Python in your next document: An extension on a recent post. |url=https://www.ds-econ.com/quarto/ |access-date=2023-01-18 |website=ds-econ |language=en |archive-date=31 January 2023 |archive-url=https://web.archive.org/web/20230131161337/https://www.ds-econ.com/quarto/ |url-status=usurped }}</ref>
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The REPL can be extended with additional modes, and has been with packages, e.g. with an [[SQL]] mode,<ref>{{Cite web |first=Chris |last=Foster |title=SQLREPL.jl |website=[[GitHub]] |date=2022-04-04 |url=https://github.com/c42f/SQLREPL.jl |access-date=2022-09-27 |archive-date=27 September 2022 |archive-url=https://web.archive.org/web/20220927085821/https://github.com/c42f/SQLREPL.jl |url-status=live }}</ref> for database access, and ''RCall.jl'' adds an {{nowrap|R mode}}, to work with the [[R (programming language)|R language]].<ref>{{Cite web |title=Getting Started · RCall.jl |url=https://juliainterop.github.io/RCall.jl/latest/gettingstarted.html#Several-Ways-to-use-RCall-1 |access-date=2022-09-27 |website=juliainterop.github.io |archive-date=4 September 2024 |archive-url=https://web.archive.org/web/20240904035201/https://juliainterop.github.io/RCall.jl/latest/gettingstarted.html#Several-Ways-to-use-RCall-1 |url-status=live }}</ref>
Julia's [[Visual Studio Code]] extension provides a fully
===Use with other languages===
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==Implementation==
Julia's core is implemented in Julia and [[C (programming language)|C]],<!-- C99, except for 0.4 needing C11 because of static asserts --> together with [[C++]] for the [[LLVM]] dependency. The code parsing, code-lowering, and bootstrapping were implemented in FemtoLisp, a [[Scheme (programming language)|Scheme]] dialect, up to version 1.10.<ref name="JeffBezanson 2019">{{Cite web | first=Jeff | last=Bezanson | title=JeffBezanson/femtolisp | website=GitHub | date=6 June 2019 | url=https://github.com/JeffBezanson/femtolisp | access-date=16 June 2019 | archive-date=22 December 2022 | archive-url=https://web.archive.org/web/20221222170835/https://github.com/JeffBezanson/femtolisp | url-status=live }}</ref> Since that version the new pure-Julia stdlib package ''JuliaSyntax.jl'' is used for the parsing (while the old one can still be chosen)<ref>{{Cite web |title=JuliaSyntax |date=2022-08-28 |url=https://github.com/JuliaLang/JuliaSyntax.jl |publisher=The Julia Programming Language |access-date=2022-08-28 |archive-date=28 August 2022 |archive-url=https://web.archive.org/web/20220828185806/https://github.com/JuliaLang/JuliaSyntax.jl |url-status=live }}</ref> which improves speed and "greatly improves parser error messages in various cases".<ref>{{Cite web |title=Enable JuliaSyntax.jl as an alternative Julia parser by c42f · Pull Request #46372 · JuliaLang/julia |url=https://github.com/JuliaLang/julia/pull/46372 |access-date=2022-08-28 |website=GitHub |language=en |archive-date=28 August 2022 |archive-url=https://web.archive.org/web/20220828185805/https://github.com/JuliaLang/julia/pull/46372 |url-status=live }}</ref> The LLVM compiler infrastructure project is used as the [[Compiler#Back end|back end]] for generating optimized [[machine code]] for all commonly
===Current and future platforms===
Julia has tier 1 [[macOS]] support, for 64-bit [[Apple Silicon]] Macs, natively (previously such [[Apple M1]]-based Macs were only supported by ''running in [[Rosetta 2]] emulation''<ref name="Apple Silicon">{{Cite web |date=2022-05-25 |title=Julia v1.7.3 has been released |url=https://discourse.julialang.org/t/julia-v1-7-3-has-been-released/81683 |access-date=2022-05-26 |website=JuliaLang |language=en |archive-date=26 May 2022 |archive-url=https://web.archive.org/web/20220526015606/https://discourse.julialang.org/t/julia-v1-7-3-has-been-released/81683 |url-status=live }}</ref><ref>{{Cite web|title=Darwin/ARM64 tracking issue · Issue #36617 · JuliaLang/julia|url=https://github.com/JuliaLang/julia/issues/36617|access-date=2020-12-08|website=GitHub|language=en|archive-date=11 November 2020|archive-url=https://web.archive.org/web/20201111014801/https://github.com/JuliaLang/julia/issues/36617|url-status=live}}</ref>), and also fully supports Intel-based Macs. [[Windows 10|Windows on ARM]] has no official support yet.
Julia has four support tiers.<ref>{{Cite web|url=https://julialang.org/downloads/#support-tiers|title=Julia Downloads|website=julialang.org|access-date=2019-05-17|archive-date=26 January 2021|archive-url=https://web.archive.org/web/20210126095723/https://julialang.org/downloads/#support-tiers|url-status=live}}</ref> All [[IA-32]] processors completely implementing the [[P6 (microarchitecture)|i686]] subarchitecture are supported and all 64-bit [[x86-64]] (aka [[amd64]]), i.e. all less than about a decade old are supported. 64-bit [[Armv8]] (and later; i.e. [[AArch64]]) processors are supported on first tier (for macOS); otherwise second tier on Linux, and ARMv7 (AArch32) on third tier<!-- , and ARMv6 were known to work with some caveats in Julia 1.0.x -->.<ref>{{Cite web |title=julia/arm.md |date=2021-10-07 |url=https://github.com/JuliaLang/julia/blob/master/doc/src/devdocs/build/arm.md |publisher=The Julia Language |quote=A list of known issues for ARM is available. |access-date=2022-05-15 |archive-date=15 May 2022 |archive-url=https://web.archive.org/web/20220515202910/https://github.com/JuliaLang/julia/blob/master/doc/src/devdocs/build/arm.md |url-status=live }}</ref> Hundreds of packages are [[general-purpose computing on graphics processing units|GPU-accelerated]]:<ref>{{Cite web |title=JuliaGPU |url=https://juliagpu.org/ |access-date=2022-11-16 |website=juliagpu.org |quote=Almost 300 packages rely directly or indirectly on Julia's GPU capabilities. |archive-date=23 May 2020 |archive-url=https://web.archive.org/web/20200523103259/https://juliagpu.org/ |url-status=live }}</ref> Nvidia GPUs have support with ''[[CUDA]].jl'' (tier 1 on 64-bit Linux and tier 2 on 64-bit Windows, the package implementing [[Parallel Thread Execution|PTX]], for compute capability 3.5 (Kepler) or higher; both require CUDA 11+, older package versions work down to CUDA 9). There are also additionally packages supporting other accelerators, such as Google's [[tensor processing unit|TPU]]s,<ref>{{Cite web|title=Julia on TPUs|date=2019-11-26|url=https://github.com/JuliaTPU/XLA.jl|publisher=JuliaTPU|access-date=2019-11-29|archive-date=30 April 2019|archive-url=https://web.archive.org/web/20190430044159/https://github.com/JuliaTPU/XLA.jl|url-status=live}}</ref> and some Intel (integrated) GPUs, through ''[[oneAPI (compute acceleration)|oneAPI.jl]]'',<ref>{{Cite web|title=Introducing: oneAPI.jl ⋅ JuliaGPU|url=https://juliagpu.org/post/2020-11-05-oneapi_0.1/|access-date=2021-09-06|website=juliagpu.org}}</ref> and AMD's GPUs have support with e.g. [[OpenCL]]; and experimental support for the AMD [[ROCm]] stack.<ref>{{Cite web|url=https://juliagpu.org/rocm/|title=AMD ROCm · JuliaGPU|website=juliagpu.org|access-date=2020-04-20|archive-date=13 June 2020|archive-url=https://web.archive.org/web/20200613154944/https://juliagpu.org/rocm/|url-status=live}}</ref>
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* NASA and the [[Jet Propulsion Laboratory]] use Julia to model spacecraft separation dynamics,<ref>{{Cite web |title=Modeling Spacecraft Separation Dynamics in Julia - Jonathan Diegelman | website=[[YouTube]] | date=9 March 2021 |url=https://www.youtube.com/watch?v=tQpqsmwlfY0 |language=en |access-date=2021-09-06 |archive-date=6 September 2021 |archive-url=https://web.archive.org/web/20210906221540/https://www.youtube.com/watch?v=tQpqsmwlfY0 |url-status=live }}</ref><ref>{{Cite web |title=Circuitscape/Circuitscape.jl |date=2020-02-25 |url=https://github.com/Circuitscape/Circuitscape.jl |publisher=Circuitscape |access-date=2020-05-26 |archive-date=30 July 2020 |archive-url=https://web.archive.org/web/20200730074511/https://github.com/Circuitscape/Circuitscape.jl |url-status=live }}</ref><ref>{{Cite web |title=Conservation through Coding: 5 Questions with Viral Shah {{!}} Science Mission Directorate |url=https://science.nasa.gov/earth-science/applied-sciences/making-space-for-earth/5-questions-with-viral-shah |access-date=2020-05-26 |website=science.nasa.gov |archive-date=25 May 2020 |archive-url=https://web.archive.org/web/20200525212814/https://science.nasa.gov/earth-science/applied-sciences/making-space-for-earth/5-questions-with-viral-shah |url-status=dead }}</ref> analyze [[TRAPPIST]] [[exoplanet]] datasets,<ref>{{Cite web |title=Julia in the Wild - Julia Data Science |url=https://juliadatascience.io/julia_wild |access-date=2022-09-12 |website=juliadatascience.io |archive-date=12 September 2022 |archive-url=https://web.archive.org/web/20220912202632/https://juliadatascience.io/julia_wild |url-status=live }}</ref><ref>{{Cite web |title=Seven Rocky TRAPPIST-1 Planets May Be Made of Similar Stuff |url=https://exoplanets.nasa.gov/news/1669/seven-rocky-trappist-1-planets-may-be-made-of-similar-stuff/ |access-date=2022-10-06 |website=Exoplanet Exploration: Planets Beyond our Solar System |date=21 January 2021 |archive-date=6 October 2022 |archive-url=https://web.archive.org/web/20221006193612/https://exoplanets.nasa.gov/news/1669/seven-rocky-trappist-1-planets-may-be-made-of-similar-stuff/ |url-status=live }}</ref> and analyze [[cosmic microwave background]] data from the [[Big Bang]]<ref>{{Cite web |title=Julia in Astronomy & Astrophysics Research {{!}} Eric B. Ford {{!}} JuliaCon 2022 | website=[[YouTube]] | date=25 July 2022 |url=https://www.youtube.com/watch?v=vj1uzilanQI |language=en |access-date=2022-10-06 |archive-date=6 October 2022 |archive-url=https://web.archive.org/web/20221006193235/https://www.youtube.com/watch?v=vj1uzilanQI |url-status=live }}</ref>
* The Brazilian [[National Institute for Space Research|INPE]], for space missions and [[satellite]] simulations<ref>{{Cite web |title=JuliaSpace/SatelliteToolbox.jl |date=2020-05-20 |url=https://github.com/JuliaSpace/SatelliteToolbox.jl |publisher=JuliaSpace |access-date=2020-05-26 |archive-date=16 June 2021 |archive-url=https://web.archive.org/web/20210616105212/https://github.com/JuliaSpace/SatelliteToolbox.jl |url-status=live }}</ref>
* Julia has also flown in space, on a small <!-- [[cubsat]] --> satellite,<ref name="space_GPS">{{Cite web |date=2024-12-13 |title=Julia and the GPS payload onboard Waratah Seed-1 satellite |url=https://discourse.julialang.org/t/julia-and-the-gps-payload-onboard-waratah-seed-1-satellite/123795 |access-date=2025-02-04 |website=Julia Programming Language |quote=We flew our GPS receiver payload, Harry v3 on Waratah Seed-1 6U cubesat [..] <!-- Julia running in space! --> Julia can also run on Raspberry Pi CM4, the processor I used on our GPS payload computer. <!-- [..] In space, we also capture IF data for us to do postprocessing in ground. --> |language=en}}</ref> used for a GPS module.<!-- https://www.reddit.com/r/Julia/comments/17vrk5r/what_are_the_most_fascinating_projects_you_have/ --> And Julia has also been used to design
* [[Embedded system|Embedded]] hardware to plan and execute flight of autonomous U.S. [[Air Force Research Laboratory]] [[VTOL]] [[unmanned aircraft system|drones]]<ref>{{Cite web |last=Hobbs |first=Kerianne |date=December 2022 |title=Year of Autonomy in Alaskan Glaciers, Flight, Earth Orbit, Cislunar Space and Mars |url=https://digitaleditions.walsworth.com/publication/?m=7270&i=769555&p=48 |publisher=Aerospace America Year in Review |page=48 |quote=The flight test team was able to demonstrate … a vertical takeoff and landing vehicle with both electric and conventional fuel propulsion systems onboard. The [[unmanned aircraft system|[uncrewed aerial system]]] was able to plan and execute these missions autonomously using onboard hardware. It was the first time the Julia programming language was flown on the embedded hardware - algorithms were precompiled ahead of time. <!-- Too much detail to also include this in footnote?: The algorithms used to perform the various missions involved feedback control, mixed-integer linear programming and optimal control. --> |access-date=26 January 2023 |archive-date=19 June 2024 |archive-url=https://web.archive.org/web/20240619193142/https://digitaleditions.walsworth.com/publication/?m=7270&i=769555&p=48 |url-status=live }}</ref>
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==See also==
{{Portal|Computer programming|Free and open-source software}}
* [[Comparison of numerical-analysis software]]
* [[Comparison of statistical packages]]
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* {{cite journal|last1=Bezanson|first1=J|last2=Edelman|first2=A|last3=Karpinski|first3=S|last4=Shah|first4=V. B|year=2017|title=Julia: A fresh approach to numerical computing|journal=SIAM Review |volume=59 |issue=1 |pages=65–98 |doi=10.1137/141000671 |arxiv=1411.1607 |citeseerx=10.1.1.760.8894|s2cid=13026838}}
* {{cite book|last=Joshi|first=Anshul|year=2016|title=Julia for Data Science － Explore the world of data science from scratch with Julia by your side|publisher=Packt |isbn=978-1-78355-386-0 |url=https://books.google.com/books?id=Bn9cDgAAQBAJ&pg=PP2}}
* Tobin A Driscoll and Richard J. Braun (Aug. 2022).
* C. T. Kelley (2022).
* {{cite book|last=Kalicharan|first=Noel|year=2021|title=Julia - Bit by Bit|series=Undergraduate Topics in Computer Science |publisher=Springer |doi=10.1007/978-3-030-73936-2 |isbn=978-3-030-73936-2 |s2cid=235917112 |url=https://link.springer.com/book/10.1007/978-3-030-73936-2 }}
* Clemens Heitzinger (2022):
* Kenneth Lange (Jun. 2025): ''Algorithms from THE BOOK'' (2nd Ed.), SIAM, ISBN 978-1-61197-838-4.
==External links==
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