Book Image

Building Python Web APIs with FastAPI

By : Abdulazeez Abdulazeez Adeshina
Book Image

Building Python Web APIs with FastAPI

By: Abdulazeez Abdulazeez Adeshina

Overview of this book

RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You’ll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you’ll have developed a solid understanding of the FastAPI framework and be able to build and deploy robust REST APIs.
Table of Contents (14 chapters)
Part 1: An Introduction to FastAPI
Part 2: Building and Securing FastAPI Applications
Part 3: Testing And Deploying FastAPI Applications

Setting up MongoDB

There are a number of libraries that allow us to integrate MongoDB into our FastAPI application. However, we’ll be using Beanie, an asynchronous Object Document Mapper (ODM) library, to execute database operations from our application.

Let’s install the beanie library by running the following command:

(venv)$ pip install beanie

Before diving into the integration, let’s look at some of the methods from the Beanie library and also how database tables are created in this section.


In SQL, the data stored in rows and columns are contained in the table. In a NoSQL database, it is called a document. The document represents how the data will be stored in the database collection. Documents are defined the same way a Pydantic model is defined, except that the Document class from the Beanie library is inherited instead.

An example document is defined as follows:

from beanie import Document
class Event(Document):