Book Image

Building Data Science Applications with FastAPI - Second Edition

By : François Voron
3 (1)
Book Image

Building Data Science Applications with FastAPI - Second Edition

3 (1)
By: François Voron

Overview of this book

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.
Table of Contents (21 chapters)
1
Part 1: Introduction to Python and FastAPI
7
Part 2: Building and Deploying a Complete Web Backend with FastAPI
13
Part 3: Building Resilient and Distributed Data Science Systems with FastAPI

Setting up testing tools for FastAPI with HTTPX

If you look at the FastAPI documentation regarding testing, you’ll see that it recommends that you use TestClient provided by Starlette. In this book, we’ll show you a different approach involving an HTTP client called HTTPX.

Why? The default TestClient is implemented in a way that makes it completely synchronous, meaning you can write tests without worrying about async and await. This might sound nice, but we found that it causes some problems in practice: since your FastAPI app is designed to work asynchronously, you’ll likely have lots of services working asynchronously, such as the database drivers we saw in Chapter 6, Databases and Asynchronous ORMs. Thus, in your tests, you’ll probably need to perform some actions on those asynchronous services, such as filling a database with dummy data, which will make your tests asynchronous anyway. Melding the two approaches often leads to strange errors that are...