Last Updated on May 22, 2022
Julia is a high-level, high-performance dynamic programming language for technical computing by Alan Edelman, Stefan Karpinski, Jeff Bezanson, and Viral Shah. 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.
1. Think Julia: How to Think Like a Computer Scientist by Allen Downey, Ben Lauwens
Julia is a unique programming language because it solves the so-called “two languages problem.” No other programming language is needed to write high-performance code. This does not mean it happens automatically. It’s the responsibility of the programmer to optimize the code that forms a bottleneck, but this can done in Julia itself.
This book is for anyone who wants to learn to program. No formal prior knowledge is required.
New concepts are introduced gradually and more advanced topics are described in later chapters.
Think Julia can be used for a one-semester course at the high school or college level.
Think Julia is available under the Creative Commons Attribution-NonCommercial 3.0 Unported License.
2. Julia Language: A Concise Tutorial by Antonello Lobianco
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.
- Getting started.
- Data types.
- Control flow.
- Custom structures.
- Input – Output.
- Managing run-time errors (exceptions).
- Interfacing Julia with other languages.
- Performances (parallelisation, debugging, profiling…).
- Developing Julia packages.
License details are not specified.
3. The Julia Express by Bogumił Kaminski
The purpose of this document is to introduce programmers to Julia programming by example. This short book is a simplified exposition of the language.
This is an introductory document. Important topics that a person learning the Julia should be aware of, that are not covered are: parametric types, parallel and distributed processing, advanced I/O operations, advanced package management, interaction with system shell, exception handling, creation of coroutines, and integration with C, Fortran, Python and R.
- Basic literals and types.
- Special literals and types;
- Programming constructs.
- Variable scoping
- Essential general usage functions.
- Reading and writing data.
- Random numbers.
- Statistics and machine learning
The Julia Express is published under the MIT License.
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