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)

Optional and keyword arguments

When defining functions, one or more arguments can be given a default value such as f(arg = val). If no parameter is supplied for arg, then val is taken as the value of arg. The position of these arguments in the function's input is important, just as it is for normal arguments; that's why they are called optional positional arguments. Here is an example of an f function with an optional argument b:

# code in arguments.jl: 
f(a, b = 5) = a + b

For example, if it's f(1), then it returns 6; f(2, 5) returns 7; and f(3) returns 8. However, calling it with f() or f(1,2,3) returns an error, because there is no matching function f with zero or three arguments. These arguments are still only defined by position: calling f(2, b = 5) raises an error as ERROR: function f does not accept keyword arguments.

Until now, arguments...