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React Anti-Patterns

You're reading from   React Anti-Patterns Build efficient and maintainable React applications with test-driven development and refactoring

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781805123972
Length 324 pages
Edition 1st Edition
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Author (1):
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Juntao Qiu Juntao Qiu
Author Profile Icon Juntao Qiu
Juntao Qiu
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Table of Contents (20) Chapters Close

Preface 1. Part 1:Introducing the Fundamentals FREE CHAPTER
2. Chapter 1: Introducing React Anti-Patterns 3. Chapter 2: Understanding React Essentials 4. Chapter 3: Organizing Your React Application 5. Chapter 4: Designing Your React Components 6. Part 2: Embracing Testing Techniques
7. Chapter 5: Testing in React 8. Chapter 6: Exploring Common Refactoring Techniques 9. Chapter 7: Introducing Test-Driven Development with React 10. Part 3: Unveiling Business Logic and Design Patterns
11. Chapter 8: Exploring Data Management in React 12. Chapter 9: Applying Design Principles in React 13. Chapter 10: Diving Deep into Composition Patterns 14. Part 4: Engaging in Practical Implementation
15. Chapter 11: Introducing Layered Architecture in React 16. Chapter 12: Implementing an End-To-End Project 17. Chapter 13: Recapping Anti-Pattern Principles 18. Index 19. Other Book You May Enjoy

Using Replace Loop with Pipeline

The Replace Loop with Pipeline refactoring technique, as the name implies, is about replacing a loop structure with a pipeline of transformations, commonly achieved by using higher-order functions or methods such as map, filter, and reduce in functional programming languages such as JavaScript.

In the case of JavaScript, the Array prototype has methods such as map, filter, and reduce that can be chained together to form a pipeline. Each of these methods receives a function as an argument and applies this function to each element in the array, effectively transforming the array in some manner.

However, keep in mind that while replacing loops with pipelines can make the code cleaner and more readable, it might not always be the most efficient option, especially when dealing with very large datasets. So, as with all refactorings, you need to balance readability and maintainability with performance requirements in cases when you need to iterate through...

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