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

Summary

In this chapter, we learned about several anti-patterns in Julia programming. When we went over details for each anti-pattern, we also figured out how to apply alternative design solutions.

We began with the piracy anti-pattern, which refers to bad practices as related to extending functions from a third-party module. For convenience, we classified piracy anti-patterns into three different types—type I, II, and III. Each type poses a different problem in causing the system to become unstable or potentially invite problems in the future.

Next, we looked into the narrow argument types anti-pattern. When function arguments are too narrowly specified, they become less reusable. Because Julia can specialize the function for various argument types, it is more beneficial to make argument types as general as possible, utilizing abstract types. We went through several design...