Ecosystem
General Computing
Build, Deploy or Embed Your Code
Julia makes it possible to build complete applications. Write web UIs withDash.jl andGenie.jl or native UIs withGtk4.jl. Pull data froma variety of databases. Build shared libraries and executables withPackageCompiler. Deploy on a webserver withHTTP.jl or embedded devices. Powerful shell integration make it easy tomanaging other processes.
Julia has foreign function interfaces forC, Fortran,C++,Python,R,Java,Mathematica,Matlab, and many other languages. Julia can also be embedded in other programs through itsembedding API. Julia'sPackageCompiler makes it possible to build binaries from Julia programs that can be integrated into larger projects. Python programs can call Julia usingjuliacall. R programs can do the same withR's JuliaCall, which is demonstrated bycalling MixedModels.jl from R. Mathematica supportscalling Julia through its External Evaluation System.
Parallel Computing
Parallel and Heterogeneous Computing
Julia is designed for parallelism, and provides built-in primitives for parallel computing at every level: instruction level parallelism,multi-threading,GPU computing, anddistributed computing. TheCeleste.jl project achieved 1.5 PetaFLOP/s on theCori supercomputer at NERSC using 650,000 cores.
The Julia compiler can also generate native code forGPUs. Packages such asDistributedArrays.jl andDagger.jl provide higher levels of abstraction for parallelism.Distributed Linear Algebra is provided by packages likeElemental.jl andTSVD.jl. MPI style parallelism is also available throughMPI.jl.
Machine Learning
Scalable Machine Learning
TheMLJ.jl package provides a unified interface to common machine learning algorithms, which includegeneralized linear models,decision trees, andclustering.Flux.jl andLux.jl are powerful packages for Deep Learning. Packages such asMetalhead.jl,ObjectDetector.jl, andTextAnalysis.jl provide ready to use pre-trained models for common tasks.AlphaZero.jl provides a high performance implementation of the reinforcement learning algorithms from AlphaZero.Turing.jl is a best in class package for probabilistic programming.
Scientific Computing
Rich Ecosystem for Scientific Computing
Julia is designed from the ground up to be very good at numerical and scientific computing. This can be seen in the abundance of scientific tooling written in Julia, such as the state-of-the-art differential equations ecosystem(DifferentialEquations.jl), optimization tools (JuMP.jl andOptimization.jl), iterative linear solvers (Krylov.jl,LinearSolve.jl), Fast Fourier transforms(AbstractFFTs.jl), and much more. General purpose simulation frameworks are available forScientific Machine Learning,Quantum computing and much more.
Julia also offers a number of domain-specific ecosystems, such as in biology (BioJulia), operations research (JuMP Dev), image processing(JuliaImages), quantum physics(QuantumBFS), nonlinear dynamics (JuliaDynamics), quantitative economics(QuantEcon), astronomy (JuliaAstro) and ecology(EcoJulia). With a set of highly enthusiastic developers and maintainers, the scientific ecosystem in Julia continues to grow rapidly.
Data Science
Interact with your Data
The Julia data ecosystem providesDataFrames.jl to work with datasets, and perform common data manipulations.CSV.jl is a fast multi-threaded package to read CSV files and integration with the Arrow ecosystem is in the works withArrow.jl. Online computations on streaming data can be performed withOnlineStats.jl. TheQueryverse provides query, file IO and visualization functionality. In addition to working with tabular data, theJuliaGraphs packages make it easy to work with combinatorial data.
Julia can work with almost all databases usingJDBC.jl andODBC.jl drivers. In addition, it also integrates with the Spark ecosystem throughSpark.jl.
Visualization
Data Visualization and Plotting
Data visualization has a complicated history. Plotting software makes trade-offs between features and simplicity, speed and beauty, and a static and dynamic interface. Some packages make a display and never change it, while others make updates in real-time.
Plots.jl is a visualization interface and toolset. It provides a common API across variousbackends, likeGR.jl,PyPlot.jl, andPlotlyJS.jl.Makie.jl is a sophisticated package for complex graphics and animations. Users who are used to "grammar of graphics" plotting APIs should take a look atGadfly.jl.VegaLite.jl provides theVega-Lite grammar of interactive graphics interface as a Julia package. For those who do not wish to leave the comfort of the terminal, there is alsoUnicodePlots.jl.
