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Hands-On Design Patterns and Best Practices with Julia: Proven solutions to common problems in software design for Julia 1.x
Design and develop high-performance, reusable, and maintainable applications using traditional and modern Julia patterns with this comprehensive guide
Key FeaturesExplore useful design patterns along with object-oriented programming in Julia 1.0Implement macros and metaprogramming techniques to make your code faster, concise, and efficientDevelop the skills necessary to implement design patterns for creating robust and maintainable applicationsBook DescriptionDesign 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.
What you will learnMaster the Julia language features that are key to developing large-scale software applicationsDiscover design patterns to improve overall application architecture and designDevelop reusable programs that are modular, extendable, performant, and easy to maintainWeigh up the pros and cons of using different design patterns for use casesExplore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniquesWho this book is forThis book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications.
Table of ContentsDesign Patterns and Related PrinciplesModules, Packages, and Data Type ConceptsDesigning Functions and InterfacesMacros and Meta Programming TechniquesReusability PatternsPerformance PatternsMaintainability PatternsRobustness PatternsMiscellaneous PatternsAnti-PatternsObject Oriented Traditional PatternsInheritance and Variance
Key FeaturesExplore useful design patterns along with object-oriented programming in Julia 1.0Implement macros and metaprogramming techniques to make your code faster, concise, and efficientDevelop the skills necessary to implement design patterns for creating robust and maintainable applicationsBook DescriptionDesign 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.
What you will learnMaster the Julia language features that are key to developing large-scale software applicationsDiscover design patterns to improve overall application architecture and designDevelop reusable programs that are modular, extendable, performant, and easy to maintainWeigh up the pros and cons of using different design patterns for use casesExplore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniquesWho this book is forThis book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications.
Table of ContentsDesign Patterns and Related PrinciplesModules, Packages, and Data Type ConceptsDesigning Functions and InterfacesMacros and Meta Programming TechniquesReusability PatternsPerformance PatternsMaintainability PatternsRobustness PatternsMiscellaneous PatternsAnti-PatternsObject Oriented Traditional PatternsInheritance and Variance
- GenresProgramming
815 pages, Kindle Edition
Published January 17, 2020
27 people are currently reading
24 people want to read
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Displaying 1 - 3 of 3 reviews
January 25, 2021
After reading this book, I feel better equipped to solve problems in Julia. It gave a thorough walkthrough of the toolkit that Julia provides, such as: parametric types, dynamic dispatch, macros, etc...
Overall, I think it was a great book. The chapters are nicely broken down, and though formulaic ("here's what I'm about to say.. I'm saying it.. here's what I said... here are some questions to verify your understanding"), I didn't find it too tedious. Kwong writes very clearly. He strives to use a variety of domains for his examples, from his go-to finance examples to video games and biology. I particularly enjoyed when he used snippets of open source libraries to show real world usage of patterns like "Holy Traits". I also appreciated how he validated the performance of different choices using Julia's benchmarking tools.
With that said, I found the title of the book (and the structure of the book, to an extent) to be a bit confusing/misleading.
The structure was roughly:
1. [1st chapter] An introduction to computer programming truisms: KISS, DRY, etc...
2. [most of book] Explaining the Julia language and best-practices to solve problems in Julia.
3. [2nd to last chapter] An overview of the "Gang of 4 Design Patterns", smooshed into one chapter which roughly said: most of these OOP concepts are trivial to solve or irrelevant in a language like Julia.
4. [last chapter] Advanced Julia topics, such as type system edge-cases... How does the type system handle functions passed as function arguments? For parametrized types, when does the compiler resolve to an abstract type (Number) vs a concrete type (Float64)?
Of particular concern for the author: when I shared this book with someone else, they had trouble getting started because section (1) was so detached from Julia applications.
--
If it's helpful to know my background to decide if this book might also click with you... I'm coming to this book as a software developer of ~10 years. I've never done work in Julia; rather, I mostly use Go and Typescript. I've toyed with Python for data science applications.
I used Julia to solve the Advent of Code puzzles in 2020 and really enjoyed the language. I read this in hopes of writing code that leverages Julia's strengths instead of writing Python-like code in Julia. I'm also trying out Julia via MIT's Computational Thinking course , which I highly recommend! https://computationalthinking.mit.edu/
Overall, I think it was a great book. The chapters are nicely broken down, and though formulaic ("here's what I'm about to say.. I'm saying it.. here's what I said... here are some questions to verify your understanding"), I didn't find it too tedious. Kwong writes very clearly. He strives to use a variety of domains for his examples, from his go-to finance examples to video games and biology. I particularly enjoyed when he used snippets of open source libraries to show real world usage of patterns like "Holy Traits". I also appreciated how he validated the performance of different choices using Julia's benchmarking tools.
With that said, I found the title of the book (and the structure of the book, to an extent) to be a bit confusing/misleading.
The structure was roughly:
1. [1st chapter] An introduction to computer programming truisms: KISS, DRY, etc...
2. [most of book] Explaining the Julia language and best-practices to solve problems in Julia.
3. [2nd to last chapter] An overview of the "Gang of 4 Design Patterns", smooshed into one chapter which roughly said: most of these OOP concepts are trivial to solve or irrelevant in a language like Julia.
4. [last chapter] Advanced Julia topics, such as type system edge-cases... How does the type system handle functions passed as function arguments? For parametrized types, when does the compiler resolve to an abstract type (Number) vs a concrete type (Float64)?
Of particular concern for the author: when I shared this book with someone else, they had trouble getting started because section (1) was so detached from Julia applications.
--
If it's helpful to know my background to decide if this book might also click with you... I'm coming to this book as a software developer of ~10 years. I've never done work in Julia; rather, I mostly use Go and Typescript. I've toyed with Python for data science applications.
I used Julia to solve the Advent of Code puzzles in 2020 and really enjoyed the language. I read this in hopes of writing code that leverages Julia's strengths instead of writing Python-like code in Julia. I'm also trying out Julia via MIT's Computational Thinking course , which I highly recommend! https://computationalthinking.mit.edu/
April 26, 2020
As a mainly self-taught programmer, I think I can program reasonably well, yet I struggle in developing larger software projects. This book is a fantastic resource outlining the practices of software architecture using Julia. It is a practical guide to making your code more robust, performant and manageable. Through dozens of examples, it illustrates the power of Julia to solve computational problems using compact, fast and readable code.
February 15, 2023
Very clearly written. The book demonstrates how one should think differently about common programming paradigms in Julia in an approachable way that doesn't assume much knowledge. I'd recommend anyone learning Julia to pick up this book after getting familiar with the syntax.
Displaying 1 - 3 of 3 reviews