Book Image

Julia 1.0 Programming. - Second Edition

By : Ivo Balbaert
Book Image

Julia 1.0 Programming. - Second Edition

By: Ivo Balbaert

Overview of this book

The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell

Map, filter, and list comprehensions

Maps and filters are typical for functional languages. A map is a function of the formmap(func, coll), where func is a (often anonymous) function that is successively applied to every element of the coll collection, so map returns a new collection. Some examples are as follows:

  • map(x -> x * 10, [1, 2, 3]) returns [10, 20, 30]
  • cubes = map(x-> Base.power_by_squaring(x, 3), collect(1:5)) returns [1, 8, 27, 64, 125]


power_by_squaring is an internal function in Base, which means it is not exported, so it has to be qualified with Base.

The map function can also be used with functions that take more than one argument. In this case, it requires a collection for each argument; for example, map(*, [1, 2, 3], [4, 5, 6]) works per element and returns [4, 10, 18].


When the function passed to map requires several lines, it can be a bit unwieldy to write as an anonymous function. For instance, consider using the following function:

map( x-> begin