Book Image

Hands-On Design Patterns and Best Practices with Julia

By : Tom Kwong
Book Image

Hands-On Design Patterns and Best Practices with Julia

By: Tom Kwong

Overview of this book

Design patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications. Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages. By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development.
Table of Contents (19 chapters)
1
Section 1: Getting Started with Design Patterns
3
Section 2: Julia Fundamentals
7
Section 3: Implementing Design Patterns
15
Section 4: Advanced Topics

Chapter 9

What predefined data type can be used to conveniently create new singleton types?

The built-in Val type can be used to create new singleton types easily. The Val constructor function can accept any bits-type value and return a singleton of type Val{X}, where X is the value being passed to the constructor function.

What are the benefits of using singleton type dispatch?

Using singleton type dispatch, we can eliminate conditional statements that depend on the data type. It also allows us to add new functionalities by just defining new functions, without having to modify an existing function. Because Julia does the dispatch natively, there is no need to create any custom function just for dispatch.

Why do we want to create stubs?

Stubs are very useful indeed in automated testing. First, if a function requires connecting to a remote web service, then it can...