Book Image

Learning Julia

By : Anshul Joshi, Rahul Lakhanpal
Book Image

Learning Julia

By: Anshul Joshi, Rahul Lakhanpal

Overview of this book

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Data Visualization and Graphics

Type annotations


In the previous chapter, we read about functions in Julia and how to statically declare the data type of the argument in a function definition. In this section, we will be focusing on type declarations and conversions, while at the same time using our newly acquired knowledge about functions in order to complement each section with examples.

Let's have a look at the following example, where we declare a simple mathematical function to find the cube of a number:

# declare the function
julia> function cube(number::Int64)
       return number ^ 3
       end
cube (generic function with 1 method)

# function call
julia> cube(10)
1000

If you follow along closely, you will notice the use of an operator, ::, along with Int64 being used while declaring this function cube. The :: is nothing but a simple operator available in Julia that lets you attach type annotations to an expression or a variable in a program. The Int64 is a type that is used to denote that the argument number...