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

Writing tests for REST API endpoints

All the tools we need to test our FastAPI application are now ready. All these tests boil down to performing an HTTP request and checking the response to see whether it corresponds to what we expect.

Let’s start simply with a test for our hello_world path operation function. You can see it in the following code:

chapter09_app_test.py

@pytest.mark.asyncioasync def test_hello_world(test_client: httpx.AsyncClient):
    response = await test_client.get("/")
    assert response.status_code == status.HTTP_200_OK
    json = response.json()
    assert json == {"hello": "world"}

First of all, notice that the test function is defined as async. As we mentioned previously, to make it work with...