Julia
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General. Julia provides asynchronous I/O, metaprogramming, debugging, logging, profiling, a package manager, and more. One can build entire Applications and Microservices in Julia. Open source. Julia is an open source project with over 1,000 contributors. It is made available under the MIT license. The source code is available on GitHub.
Julia is a high-level, general-purpose [23] dynamic programming language, most commonly used for numerical analysis and computational science.
Install the latest Julia version ( v1.10.4 June 4, 2024) by running this in your terminal: curl -fsSL https://install.julialang.org | sh. It looks like you're using a Unix-type system. For Windows instructions click here. Once installed julia will be available via the command line interface.
Julia is a language that is fast, dynamic, easy to use, and open source. Click here to learn more.
Julia provides ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general programming.
The easiest way to learn and experiment with Julia is by starting an interactive session (also known as a read-eval-print loop or "REPL") by double-clicking the Julia executable or running julia from the command line:
Introduction. Julia Base contains a range of functions and macros appropriate for performing scientific and numerical computing, but is also as broad as those of many general purpose programming languages. Additional functionality is available from a growing collection of available packages.
The Julia project thrives on the efforts of it's community to help improve the project. We'd love to help you get involved too! This guide is a comprehensive resource for new and experienced contributors alike.
Julia is a high-performance, dynamic programming language for modern technical computing. It solves the two language problem by being simultaneously as fast as C and as easy as Python.
Julia is an open-source, multi-platform, high-level, high-performance programming language for technical computing. Julia has an LLVM -based JIT compiler that allows it to match the performance of languages such as C and FORTRAN without the hassle of low-level code.
