What is Julia?
Julia is a high-level, high-performance dynamic programming language for technical computing. Julia aims to create an unprecedented combination of ease-of-use, power, and efficiency in a single language.
It’s a homoiconic functional language focused on technical computing. While having the full power of homoiconic macros, first-class functions, and low-level control, Julia is as easy to learn and use as Python.
Although Julia is a new language, first appearing in 2012, its roots are in Lisp, so it comes with mature features like macros and support for other metaprogramming techniques like code generation. Julia’s expressive grammar lets you write easy-to-read and easier-to-debug code, and its speed gets you through more work in less time. It’s a great choice whether you’re designing a machine learning system, crunching statistical data, or writing system utilities.
Distinctive aspects of Julia’s design include a type system with parametric polymorphism and types in a fully dynamic programming language and multiple dispatch as its core programming paradigm. It allows concurrent, parallel and distributed computing, and direct calling of C and Fortran libraries without glue code.
Because Julia is a new language there are relatively limited resources to help you get started with it besides the official documentation. But we’ve researched the finest open source resources to help you master the language.
By The Julia Project (998 pages)
This is the official documentation for Julia. It goes into great depth about the language.
This comprehensive book covers everything from strings, functions, control flow, types, methods, constructors, modules, to mulit-dimensional arrays, networking, global variables, environment variables, embedding Julia and so much more.
The Julia language is licensed under the MIT License.
By Bogumił Kaminski (13 pages)
The purpose of this document is to introduce programmers to Julia programming by example. This short book is a simplified exposition of the language.
The Julia Express is published under the MIT License.
By Bogumił Kaminski
An Introduction to DataFrames offers readers a valuable insight into using DataFrames.
This tutorial covers:
The tutorial works with Julia 1.0.
The book is published under the MIT License.
By Samuel Colvin (–)
This is a set of articles that offer examples of Julia, the high-level, high-performance dynamic programming language for technical computing.
This work is published under the MIT License.
By Leah Hanson and many contributors (Web page)
This tutorial covers the following topics:
This work is published under the Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) License.
By Antonello Lobianco (65 pages)
The purposes of this tutorial are (a) to store things the author has learned himself about Julia and (b) to help those who want to start coding in Julia before reading official documentation.
License details are not specified.
Other useful Julia resources:
- A Deep Introduction to Julia for Data Science and Scientific Computing
- Quantecon tutorial – This work is released under a Creative Commons Attribution-NoDerivatives 4.0 International License.