Julia (programming language)
- Multiple dispatch: providing ability to define function behavior across many combinations of argument types
- Dynamic type system: types for documentation, optimization, and dispatch
- Good performance, approaching that of statically-typed languages like C
- A built-in package manager
- Lisp-like macros and other metaprogramming facilities
- Call Python functions: use the PyCall package[b]
- Call C functions directly: no wrappers or special APIs
- Powerful shell-like abilities to manage other processes
- Designed for parallel and distributed computing
- Coroutines: lightweight green threading
- User-defined types are as fast and compact as built-ins
- Automatic generation of efficient, specialized code for different argument types
- Elegant and extensible conversions and promotions for numeric and other types
- Efficient support for Unicode, including but not limited to UTF-8
+are generic. Dylan's type system, however, does not fully support parametric types, which are more typical of the ML lineage of languages. By default, CLOS does not allow for dispatch on Common Lisp's parametric types; such extended dispatch semantics can only be added as an extension through the CLOS Metaobject Protocol. By convergent design, Fortress also features multiple dispatch on parametric types; unlike Julia, however, Fortress is statically rather than dynamically typed, with separate compiling and executing phases. The language features are summarized in the following table:
|Language||Type system||Generic functions||Parametric types|
|Common Lisp||Dynamic||Opt-in||Yes (but no dispatch)|
|Dylan||Dynamic||Default||Partial (no dispatch)|
?after the prompt (preceding each command), respectively. It also keeps the history of commands, including between sessions. Code that can be tested inside the Julia's interactive section or saved into a file with a
.jlextension and run from the command line by typing:
Use with other languages
ccallkeyword is used to call C-exported or Fortran shared library functions individually.
Current and future platforms
Julia Computing company
- [With Rebugger.jl] you can:
- test different modifications to the code or arguments as many times as you want; you are never forced to exit “debug mode” and save your file
- run the same chosen block of code repeatedly (perhaps trying out different ways of fixing a bug) without needing to repeat any of the “setup” work that might have been necessary to get to some deeply nested method in the original call stack.
- For calling the newer Python 3 (the older default to call Python 2, is also still supported) (and PyPy) and calling in the other direction, from Python to Julia, is also supported with pyjulia.
- "Smoothing data with Julia's @generated functions". 5 November 2015. Retrieved 9 December 2015.
Julia's generated functions are closely related to the multistaged programming (MSP) paradigm popularized by Taha and Sheard, which generalizes the compile time/run time stages of program execution by allowing for multiple stages of delayed code execution.
- "LICENSE.md". GitHub.
- "Contributors to JuliaLang/julia". GitHub.
- "Why We Created Julia". Julia website. February 2012. Retrieved 7 February 2013.
- "v1.1.0". Github.com. 21 January 2019. Retrieved 22 January 2019.
- "Set VERSION to 1.3-DEV by ararslan · Pull Request #31660 · JuliaLang/julia". GitHub. Retrieved 10 April 2019.
- "Julia". Julia. NumFocus project. Retrieved 9 December 2016.
Julia's Base library, largely written in Julia itself, also integrates mature, best-of-breed open source C and Fortran libraries for ...
- "Non-GPL Julia?". Groups.google.com. Retrieved 31 May 2017.
- "Introduce USE_GPL_LIBS Makefile flag to build Julia without GPL libraries".
Note that this commit does not remove GPL utilities such as git and busybox that are included in the Julia binary installers on Mac and Windows. It allows building from source with no GPL library dependencies.
- "Home · The Julia Language". docs.julialang.org. Retrieved 15 August 2018.
- "Programming Language Network". GitHub. Retrieved 6 December 2016.
- "JuliaCon 2016". JuliaCon. Retrieved 6 December 2016.
He has co-designed the programming language Scheme, which has greatly influenced the design of Julia
- "The Julia Language" (official website).
General Purpose [..] Julia lets you write UIs, statically compile your code, or even deploy it on a webserver.
- Bryant, Avi (15 October 2012). "Matlab, R, and Julia: Languages for data analysis". O'Reilly Strata. Archived from the original on 26 April 2014.
- Singh, Vicky (23 August 2015). "Julia Programming Language – A True Python Alternative". Technotification.
- Krill, Paul (18 April 2012). "New Julia language seeks to be the C for scientists". InfoWorld.
- Finley, Klint (3 February 2014). "Out in the Open: Man Creates One Programming Language to Rule Them All". Wired.
- Green, Todd (10 August 2018). "Low-Level Systems Programming in High-Level Julia". Archived from the original on 5 November 2018. Retrieved 5 November 2018.
- Moss, Robert (26 June 2015). "Using Julia as a Specification Language for the Next-Generation Airborne Collision Avoidance System". Archived from the original on 1 July 2015. Retrieved 29 June 2015.
- Fischer, Keno (3 February 2019), Running julia on wasm., retrieved 9 February 2019
- "Getting Started with Node Julia · Node Julia". Node-julia.readme.io. Retrieved 31 May2017.
- Fischer, Keno; Nash, Jameson. "Growing a Compiler - Getting to Machine Learning from a General Purpose Compiler". Julia Computing Blog. Retrieved 11 April 2019.
- "Suspending Garbage Collection for Performance...good idea or bad idea?". Groups.google.com. Retrieved 31 May 2017.
- (now available with
using FFTWin current versions; that dependency is one of many moved out of the standard library to a package because it is GPL licensed, and thus is not included in Julia 1.0 by default.) "Remove the FFTW bindings from Base by ararslan · Pull Request #21956 · JuliaLang/julia". GitHub. Retrieved 1 March 2018.
- "ANN: linter-julia plugin for Atom / Juno". JuliaLang. 15 February 2017. Retrieved 10 April 2019.
- "A Julia interpreter and debugger". julialang.org. Retrieved 10 April 2019.
- "[ANN] Rebugger: interactive debugging for Julia 0.7/1.0". JuliaLang. 21 August 2018. Retrieved 10 April 2019.
- "Home · Rebugger.jl". timholy.github.io. Retrieved 10 April 2019.
- Jeff Bezanson, Stefan Karpinski, Viral Shah, Alan Edelman. "Why We Created Julia". JuliaLang.org. Retrieved 5 June 2017.
- Stefan Karpinski, New Julia language seeks to be the C for scientists, Infoworld, 18 April 2012
- Torre, Charles. "Stefan Karpinski and Jeff Bezanson on Julia". Channel 9. MSDN. Retrieved 4 December 2018.
- "Julia Computing Newsletter, Growth Metrics". juliacomputing.com. Retrieved 11 February 2019.
- "JuliaCon website". juliacon.org. Retrieved 10 May 2018.
- The Julia Blog
- "What is Julia 0.7? How does it relate to 1.0?". JuliaLang. Retrieved 17 October 2018.
- Eric Davies. "Writing Iterators in Julia 0.7". julialang.org. Retrieved 5 August 2018.
- The Julia Language: A fresh approach to technical computing.: JuliaLang/julia, The Julia Language, 22 January 2019, retrieved 22 January 2019
- "JuliaCon 2017". juliacon.org. Retrieved 4 June 2017.
- Fisher, Keno. "The Celeste Project". juliacon.org. Retrieved 24 June 2017.
- Regier, Jeffrey; Pamnany, Kiran; Giordano, Ryan; Thomas, Rollin; Schlegel, David; McAulife, Jon; Prabat (2016). "Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference". arXiv:1611.03404 [cs.DC].
- Claster, Andrew (12 September 2017). "Julia Joins Petaflop Club". Julia Computing(Press release).
Celeste is written entirely in Julia, and the Celeste team loaded an aggregate of 178 terabytes of image data to produce the most accurate catalog of 188 million astronomical objects in just 14.6 minutes [..] a performance improvement of 1,000x in single-threaded execution.
- "Julia language co-creators win James H. Wilkinson Prize for Numerical Software". MIT News. Retrieved 22 January 2019.
- The Julia Language: A fresh approach to technical computing.: JuliaLang/julia, The Julia Language, 26 January 2019, retrieved 26 January 2019
- "Julia Sponsors, Research, and Publications".
- "PyCall.jl". stevengj. github.com.
- "Using PyCall in julia on Ubuntu with python3". julia-users at Google Groups.
to import modules (e.g., python3-numpy)
- "Polyglot.jl". wavexx. github.com.
- "python interface to julia".
- "Learn Julia in Y Minutes". Learnxinyminutes.com. Retrieved 31 May 2017.
- Daly, Nathan (13 February 2019), Compile, bundle, and release julia software. Contribute to NHDaly/ApplicationBuilder.jl development by creating an account on GitHub, retrieved 15 February 2019
- Compile your Julia Package. Contribute to JuliaLang/PackageCompiler.jl development by creating an account on GitHub, The Julia Language, 14 February 2019, retrieved 15 February 2019
- "Getting Started · The Julia Language". docs.julialang.org. Retrieved 15 August 2018.
- See also: https://docs.julialang.org/en/stable/manual/strings/ for string interpolation and the
string(greet, ", ", whom, ".\n")example for preferred ways to concatenate strings. Julia has the println and print functions, but also a @printf macro (i.e., not in function form) to eliminate run-time overhead of formatting (unlike the same function in C).
- "Julia Documentation". JuliaLang.org. Retrieved 18 November 2014.
- "Project Jupyter".
- "Julia: A Fast Dynamic Language for Technical Computing" (PDF). 2012.
- "How To Make Python Run As Fast As Julia". 2015.
- "Basic Comparison of Python, Julia, R, Matlab and IDL". 2015.
- Gibbs, Mark (9 January 2013). "Pure and Julia are cool languages worth checking out". Network World (column). Retrieved 7 February 2013.
- "Support MCJIT". Github.com. Retrieved 26 May 2015.
- "Using MCJIT with the Kaleidoscope Tutorial". 22 July 2013. Retrieved 26 May 2015.
The older implementation (llvm::JIT) is a sort of ad hoc implementation that brings together various pieces of the LLVM code generation and adds its own glue to get dynamically generated code into memory one function at a time. The newer implementation (llvm::MCJIT) is heavily based on the core MC library and emits complete object files into memory then prepares them for execution.
- julia: The Julia Language: A fresh approach to technical computing, The Julia Language, 1 February 2018, retrieved 1 February 2018,
A list of known issues for ARM is available.
- "Julia available in Raspbian on the Raspberry Pi".
Julia works on all the Pi variants, we recommend using the Pi 3.
- "Julia language for Raspberry Pi". Raspberry Pi Foundation.
- "About Us – Julia Computing". juliacomputing.com. Retrieved 12 September 2017.
|Wikibooks has a book on the topic of: Introducing Julia|