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Building Data Science Applications with FastAPI - Second Edition

You're reading from  Building Data Science Applications with FastAPI - Second Edition

Product type Book
Published in Jul 2023
Publisher Packt
ISBN-13 9781837632749
Pages 422 pages
Edition 2nd Edition
Languages
Author (1):
François Voron François Voron
Profile icon François Voron

Table of Contents (21) Chapters

Preface 1. Part 1: Introduction to Python and FastAPI
2. Chapter 1: Python Development Environment Setup 3. Chapter 2: Python Programming Specificities 4. Chapter 3: Developing a RESTful API with FastAPI 5. Chapter 4: Managing Pydantic Data Models in FastAPI 6. Chapter 5: Dependency Injection in FastAPI 7. Part 2: Building and Deploying a Complete Web Backend with FastAPI
8. Chapter 6: Databases and Asynchronous ORMs 9. Chapter 7: Managing Authentication and Security in FastAPI 10. Chapter 8: Defining WebSockets for Two-Way Interactive Communication in FastAPI 11. Chapter 9: Testing an API Asynchronously with pytest and HTTPX 12. Chapter 10: Deploying a FastAPI Project 13. Part 3: Building Resilient and Distributed Data Science Systems with FastAPI
14. Chapter 11: Introduction to Data Science in Python 15. Chapter 12: Creating an Efficient Prediction API Endpoint with FastAPI 16. Chapter 13: Implementing a Real-Time Object Detection System Using WebSockets with FastAPI 17. Chapter 14: Creating a Distributed Text-to-Image AI System Using the Stable Diffusion Model 18. Chapter 15: Monitoring the Health and Performance of a Data Science System 19. Index 20. Other Books You May Enjoy

Summary

Well done! You’re now acquainted with all the basic features of FastAPI. Throughout this chapter, you learned how to create and run API endpoints where you can validate and retrieve data from all parts of an HTTP request: the path, the query, the parameters, the headers, and, of course, the body. You also learned how to tailor the HTTP response to your needs, whether it is a simple JSON response, an error, or a file to download. Finally, you looked at how to define separate API routers and include them in your main application to keep a clean and maintainable project structure.

You have enough knowledge now to start building your own API with FastAPI. In the next chapter, we’ll focus on Pydantic models. You now know that they are at the core of the data validation features of FastAPI, so it’s crucial to fully understand how they work and how to manipulate them efficiently.

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