Julia
E17648
compiled programming language
dynamic programming language
high-level programming language
numerical computing language
programming language
scientific computing language
Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
Aliases (2)
Statements (79)
| Predicate | Object |
|---|---|
| instanceOf |
compiled programming language
→
dynamic programming language → high-level programming language → numerical computing language → programming language → scientific computing language → |
| basedOn |
LLVM
→
|
| compilesTo |
native machine code
→
|
| designedFor |
data science
→
numerical computing → scientific research → |
| domain |
data science
→
machine learning → numerical analysis → optimization → scientific simulation → |
| goal |
combine ease of dynamic languages with speed of compiled languages
→
|
| hasExecutionModel |
JIT-compiled
→
|
| hasFeature |
automatic differentiation support via packages
→
built-in support for arbitrary-precision arithmetic → built-in support for complex numbers → coroutines (Tasks) → distributed computing support → first-class functions → foreign function interface → garbage collection → interactive REPL → just-in-time compilation → metaprogramming with generated functions → metaprogramming with macros → multiple dispatch → multiple return values → package manager → parametric types → type inference → |
| hasFileExtension |
.jl
→
|
| hasPackageRepository |
General registry
→
|
| hasStandardImplementation |
reference implementation in Julia language itself
→
|
| hasStandardLibrary |
Base
→
Core → Distributed → LinearAlgebra → Random → SparseArrays → Statistics → Test → |
| hasSyntaxSimilarityTo |
Matlab
→
Python → |
| influenced |
scientific computing ecosystem
→
|
| influencedBy |
C
→
Lisp → Lua → Matlab → Perl → Python → R → Ruby → |
| paradigm |
multi-paradigm
→
|
| supports |
GPU computing via packages
→
Unicode identifiers → calling C and Fortran libraries → calling Python libraries via PyCall → generic programming → immutable types → metaprogramming → modules and namespaces → multiple dispatch → multiple dispatch-based polymorphism → mutable types → parallel computing → unit testing via Test standard library → user-defined types → |
| supportsParadigm |
functional programming
→
metaprogramming → object-oriented programming (via multiple dispatch) → procedural programming → |
| typingDiscipline |
dynamic typing
→
optional type annotations → strong typing → |
Referenced by (11)
| Subject (surface form when different) | Predicate |
|---|---|
|
Fortran
→
Go → Lisp → Python → |
influenced |
|
Julia Louis-Dreyfus
→
Julia Ward Howe → |
givenName |
|
Plotly
→
|
programmingLanguage |
|
Plotly
("Julia REPL")
→
|
supportsEnvironment |
|
Jupyter Notebook
→
|
supportsLanguage |
|
LLVM
("Julia (via Julia compiler)")
→
|
supportsLanguageFrontend |
|
Unicode Scalar Values
→
|
usedInProgrammingLanguage |