Book Image

Building Python Microservices with FastAPI

By : Sherwin John C. Tragura
3 (2)
Book Image

Building Python Microservices with FastAPI

3 (2)
By: Sherwin John C. Tragura

Overview of this book

FastAPI is an Asynchronous Server Gateway Interface (ASGI)-based framework that can help build modern, manageable, and fast microservices. Because of its asynchronous core platform, this ASGI-based framework provides the best option when it comes to performance, reliability, and scalability over the WSGI-based Django and Flask. When working with Python, Flask, and Django microservices, you’ll be able to put your knowledge to work with this practical guide to building seamlessly manageable and fast microservices. You’ll begin by understanding the background of FastAPI and learning how to install, configure, and use FastAPI to decompose business units. You’ll explore a unique and asynchronous REST API framework that can provide a better option when it comes to building microservices. After that, this book will guide you on how to apply and translate microservices design patterns in building various microservices applications and RESTful APIs using the FastAPI framework. By the end of this microservices book, you’ll be able to understand, build, deploy, test, and experiment with microservices and their components using the FastAPI framework.
Table of Contents (17 chapters)
1
Part 1: Application-Related Architectural Concepts for FastAPI microservice development
6
Part 2: Data-Centric and Communication-Focused Microservices Concerns and Issues
11
Part 3: Infrastructure-Related Issues, Numerical and Symbolic Computations, and Testing Microservices

Building message-driven transactions using RabbitMQ

RabbitMQ is a lightweight asynchronous message broker that supports multiple messaging protocols such as AMQP, STOM, WebSocket, and MQTT. It requires erlang before it works properly in Windows, Linux, or macOS. Its installer can be downloaded from https://www.rabbitmq.com/download.html.

Creating the Celery instance

Instead of using Redis as the broker, RabbitMQ is a better replacement as a message broker that will mediate messages between the client and the Celery worker threads. For multiple tasks, RabbitMQ can command the Celery worker to work on these tasks one at a time. The RabbitMQ broker is good for huge messages and it saves these messages to disk memory.

To start, we need to set up a new Celery instance that will utilize the RabbitMQ message broker using its guest account. We will use the AMQP protocol as the mechanism for a producer/consumer type of messaging setup. Here is the snippet that will replace the previous...