Book Image

Building Data Science Applications with FastAPI

By : François Voron
5 (1)
Book Image

Building Data Science Applications with FastAPI

5 (1)
By: François Voron

Overview of this book

FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.
Table of Contents (19 chapters)
1
Section 1: Introduction to Python and FastAPI
7
Section 2: Build and Deploy a Complete Web Backend with FastAPI
13
Section 3: Build a Data Science API with Python and FastAPI

Deploying a FastAPI application on a serverless platform

In recent years, serverless platforms have gained a lot of popularity and have become a very common way to deploy web applications. Those platforms completely hide the complexity of setting up and managing a server, giving you the tools to automatically build and deploy your application in minutes. Google App Engine, Heroku, and Azure App Service are among the most popular. Even though they have their own specificities, all these serverless platforms work on the same principles. This is why, in this section, we'll outline the common steps you should follow.

Usually, serverless platforms expect you to provide the source code in the form of a GitHub repository, which you push directly to their servers or that they pull automatically from GitHub. Here, we'll assume that you have a GitHub repository with the source code structured like so:

Figure 10.1 – Project structure for serverless deployment...