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

Summary

Congratulations! You’ve learned about another important aspect of FastAPI: designing and managing data models with Pydantic. You should now be confident about creating models and applying validation at the field level, with built-in options and types, and also by implementing your own validation methods. You also know how to apply validation at the object level to check consistency between several fields. You also learned how to leverage model inheritance to prevent code duplication and repetition while defining your model variations. Finally, you learned how to correctly work with Pydantic model instances in order to transform and update them in an efficient and readable way.

You know almost all the features of FastAPI by now. There is one last very powerful feature for you to learn about: dependency injection. This allows you to define your own logic and values and directly inject them into your path operation functions, as you do for path parameters and payload...

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