You're reading from Building Data Science Applications with FastAPI Develop, manage, and deploy efficient machine learning applications with Python

Product type Paperback

Published in Jul 2023

Publisher Packt

ISBN-13 9781837632749

Length 422 pages

Edition 2nd Edition

Languages

Python

Tools

FastAPI

Concepts

Data Science

Author (1):

François Voron

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Table of Contents (21) Chapters

Preface

1. Part 1: Introduction to Python and FastAPI

2. Chapter 1: Python Development Environment Setup FREE CHAPTER

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

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20. Other Books You May Enjoy

To get the most out of this book

In this book, we’ll mainly work with the Python programming language. The first chapter will explain how to set up a proper Python environment on your operating system. Some examples also involve running web pages with JavaScript, so you’ll need a modern browser such as Google Chrome or Mozilla Firefox.

In Chapter 14, we’ll run the Stable Diffusion model, which requires a powerful machine. We recommend a computer with 16 GB of RAM and a modern NVIDIA GPU to be able to generate good-looking images.

Software/hardware covered in the book	Operating system requirements
Python 3.10+	Windows, macOS, or Linux
Javascript	Windows, macOS, or Linux

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