Book Image

Julia 1.0 Programming Complete Reference Guide

By : Ivo Balbaert, Adrian Salceanu
Book Image

Julia 1.0 Programming Complete Reference Guide

By: Ivo Balbaert, Adrian Salceanu

Overview of this book

Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: • Julia 1.0 Programming - Second Edition by Ivo Balbaert • Julia Programming Projects by Adrian Salceanu
Table of Contents (18 chapters)

Parametric types and methods

An array can take elements of different types. Therefore, we can have, for example, arrays of the following types: Array{Int64,1}, Array{Int8,1}, Array{Float64,1}, or Array{String, 1}, and so on. That is why an Array is a parametric type; its elements can be of any arbitrary type T, written as Array{T, 1}.

In general, types can take type parameters, so that type declarations actually introduce a whole family of new types. Returning to the Point example of the previous section, we can generalize it to the following:

# see the code in Chapter 6\parametric.jl
mutable struct Point{T}
x::T
y::T
end

This is conceptually similar to the generic types in Java or templates in C++.

This abstract type creates a whole family of new possible concrete types (but they are only compiled as needed at runtime), such as Point{Int64}, Point{Float64}, and Point{String...