Book Image

Julia 1.0 Programming Cookbook

By : Bogumił Kamiński, Przemysław Szufel
Book Image

Julia 1.0 Programming Cookbook

By: Bogumił Kamiński, Przemysław Szufel

Overview of this book

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data
Table of Contents (18 chapters)
Title Page
Copyright and Credits
About Packt

Scope of variables in Julia

In this chapter, we will illustrate some variable scoping issues that might not be obvious to all Julia users. A variable can be defined in one of two scopes—either local or global. 

Getting ready

For this recipe, you do not need to install any packages.


In the GitHub repository for this recipe you will find the commands.txt file that contains the presented sequence of Julia commands.

How to do it...

To test how variable scoping works in Julia, follow the steps:

  1. Firstly, to illustrate variable scoping in Julia, run the following code:
julia>a, b=1, 2;

julia>leta=30, b=40
println("inner scope $a $b")
println("outer scope $a $b")

julia>println("global scope $a $b")

We can see that with each scoping level (created by a let...end block), the meaning of variables changes. The let statement creates a new scope for variables.

  1. Observe the following code: