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Web API Development with ASP.NET Core 8

You're reading from Web API Development with ASP.NET Core 8 Learn techniques, patterns, and tools for building high-performance, robust, and scalable web APIs

Product type Paperback

Published in Apr 2024

Publisher Packt

ISBN-13 9781804610954

Length 804 pages

Edition 1st Edition

Languages

C#

Tools

.NET Core

Concepts

Web Services

Author (1):

Xiaodi Yan

View More author details

Table of Contents (20) Chapters

Preface

1. Chapter 1: Fundamentals of Web APIs

2. Chapter 2: Getting Started with ASP.NET Core Web APIs FREE CHAPTER

3. Chapter 3: ASP.NET Core Fundamentals (Part 1)

4. Chapter 4: ASP.NET Core Fundamentals (Part 2)

5. Chapter 5: Data Access in ASP.NET Core (Part 1: Entity Framework Core Fundamentals)

6. Chapter 6: Data Access in ASP.NET Core (Part 2 – Entity Relationships)

7. Chapter 7: Data Access in ASP.NET Core (Part 3: Tips)

8. Chapter 8: Security and Identity in ASP.NET Core

9. Chapter 9: Testing in ASP.NET Core (Part 1 – Unit Testing)

10. Chapter 10: Testing in ASP.NET Core (Part 2 – Integration Testing)

11. Chapter 11: Getting Started with gRPC

12. Chapter 12: Getting Started with GraphQL

13. Chapter 13: Getting Started with SignalR

14. Chapter 14: CI/CD for ASP.NET Core Using Azure Pipelines and GitHub Actions

15. Chapter 15: ASP.NET Core Web API Common Practices

16. Chapter 16: Error Handling, Monitoring, and Observability

17. Chapter 17: Cloud-Native Patterns

18. Index

Why subscribe?

19. Other Books You May Enjoy

Who this book is for

This book is for developers who want to learn how to build web APIs with ASP.NET Core 8 and create flexible, maintainable, scalable applications with the .NET platform. Prior basic knowledge of C#, .NET, and Git would be helpful.

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Authors (1)

Yan

Yan

James Yan is an undergraduate student at the University of Toronto (UofT), currently double-majoring in computer science and statistics. He has hands-on knowledge of Python, R, Java, MATLAB, and SQL. During his study at UofT, he has taken many related courses, such as Methods of Data Analysis I and II, Methods of Applied Statistics, Introduction to Databases, Introduction to Artificial Intelligence, and Numerical Methods, including a capstone course on AI in clinical medicine.

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