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

Chapter 6. More on Types, Methods, and Modules

Julia has a rich built-in type system, and most data types can be parameterized, such as Array{Float64, 2} or Dict{Symbol, Float64}. Typing a variable (or more exactly the value it is bound to) is optional. However, indicating the type of some variables, although they are not statically checked, can provide some of the advantages of static-type systems as in C++, Java, or C#. A Julia program can run without any indication of types, which can be useful in a prototyping stage, and it will still run fast. However, some type indications can increase the performance by allowing more specialized multiple dispatch. Type assertions also help the LLVM compiler to create more compact, better optimized code. Moreover, typing function parameters makes the code easier to read and understand. The robustness of the program is also enhanced by throwing exceptions, in cases where certain type operations are not allowed. These failures will manifest themselves...