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

Validating request bodies using Pydantic models

In FastAPI, request bodies can be validated to ensure only defined data is sent. This is crucial, as it serves to sanitize request data and reduce malicious attacks’ risks. This process is known as validation.

A model in FastAPI is a structured class that dictates how data should be received or parsed. Models are created by subclassing Pydantic’s BaseModel class.

What is Pydantic?

Pydantic is a Python library that handles data validation using Python-type annotations.

Models, when defined, are used as type hints for request body objects and request-response objects. In this chapter, we will only look at using Pydantic models for request bodies.

An example model is as follows:

from pydantic import BaseModel
class PacktBook(BaseModel):
    id: int
    Name: str
    Publishers: str
    Isbn: str

In the preceding code block...