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Learning Julia

You're reading from   Learning Julia Build high-performance applications for scientific computing

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781785883279
Length 316 pages
Edition 1st Edition
Languages
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Authors (2):
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Rahul Lakhanpal Rahul Lakhanpal
Author Profile Icon Rahul Lakhanpal
Rahul Lakhanpal
Anshul Joshi Anshul Joshi
Author Profile Icon Anshul Joshi
Anshul Joshi
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Table of Contents (11) Chapters Close

Preface 1. Understanding Julia's Ecosystem FREE CHAPTER 2. Programming Concepts with Julia 3. Functions in Julia 4. Understanding Types and Dispatch 5. Working with Control Flow 6. Interoperability and Metaprogramming 7. Numerical and Scientific Computation with Julia 8. Data Visualization and Graphics 9. Connecting with Databases 10. Julia’s Internals

Understanding Julia's Ecosystem

Julia is a new programming language compared to other existing popular programming languages. Julia was presented publicly to the world and became open source in February of 2012. It all started in 2009, when three developers—Viral Shah, Stefan Karpinski, and Jeff Bezanson at the Massachusetts Institute of Technology (MIT), under the supervision of Professor Alan Edelman in the Applied Computing groupstarted working on a project. This lead to Julia. All of the principal developers are still actively involved with the JuliaLang. They are committed not just to the core language but to the different libraries that have evolved in its ecosystem. Julia is based on solid principles, which we will learn throughout the book. It is becoming more famous day by day, continuously gaining in the ranks of the TIOBE index (currently at 43), and gaining traction on Stack Overflow. Researchers are attracted to it, especially those from a scientific computing background.

Anyone can check the source code, which is available on GitHub (https://github.com/JuliaLang/julia). The current release at the time of writing this book is 0.6 with 633 contributors, 39,010 commits, and 9,398 stars on GitHub. Most of the core is written in Julia itself and there are a few chunks of code in C/C++, Lisp, and Scheme.

This chapter will take you through the installation and a basic understanding of all the necessary components of Julia. This chapter covers the following topics:

  • What makes Julia unique?
  • Installing Julia
  • Julia's importance in data science
  • Using REPL
  • Using Jupyter Notebook
  • What is Juno?
  • Package management
  • A brief about multiple dispatch
  • Understanding LLVM and JIT
You have been reading a chapter from
Learning Julia
Published in: Nov 2017
Publisher: Packt
ISBN-13: 9781785883279
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