Anonymous Functions - Julia Typing CST Test
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Anonymous Functions — Julia Code
Using anonymous functions and broadcasting.
add = (x,y) -> x + y
println(add(3,7))Julia Language Guide
Julia is a high-performance, dynamic programming language built for numerical computing, scientific computation, data science, and machine learning. It offers the speed of C with the ease of Python, featuring JIT compilation, multiple dispatch, and built-in parallelism.
Primary Use Cases
- ▸Scientific computing
- ▸Numerical simulations
- ▸Machine learning & data science
- ▸Optimization problems
- ▸High-performance computing (HPC)
- ▸GPU programming
- ▸Differential equations & modeling
Notable Features
- ▸Multiple dispatch
- ▸JIT compilation via LLVM
- ▸Python-like syntax with C-like speed
- ▸Built-in package manager (Pkg)
- ▸Native parallel & distributed computing
Origin & Creator
Created in 2009 by Jeff Bezanson, Stefan Karpinski, Viral Shah, and Alan Edelman; first stable release (1.0) came out in 2018.
Industrial Note
Julia dominates niches requiring extreme numerical throughput: computational physics, climate modeling, optimization engines, simulations, automatic differentiation, GPU programming, and probabilistic programming (Turing.jl).