Book Image

Python Microservices Development – 2nd edition - Second Edition

By : Simon Fraser, Tarek Ziadé
Book Image

Python Microservices Development – 2nd edition - Second Edition

By: Simon Fraser, Tarek Ziadé

Overview of this book

The small scope and self-contained nature of microservices make them faster, cleaner, and more scalable than code-heavy monolithic applications. However, building microservices architecture that is efficient as well as lightweight into your applications can be challenging due to the complexity of all the interacting pieces. Python Microservices Development, Second Edition will teach you how to overcome these issues and craft applications that are built as small standard units using proven best practices and avoiding common pitfalls. Through hands-on examples, this book will help you to build efficient microservices using Quart, SQLAlchemy, and other modern Python tools In this updated edition, you will learn how to secure connections between services and how to script Nginx using Lua to build web application firewall features such as rate limiting. Python Microservices Development, Second Edition describes how to use containers and AWS to deploy your services. By the end of the book, you’ll have created a complete Python application based on microservices.
Table of Contents (14 chapters)
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Running all microservices

So far, we have run our Quart applications using the built-in Quart wrapper, or using the run() function. This works well for development, as the app can detect changes to its source code and reload itself, saving time when making changes. However, there are limitations to this, not least of which is that this is running the server in a development mode, with extra diagnostics turned on that slow down the server's operation.

Instead, we should run our applications using Hypercorn (, an ASGI web server that allows Quart to run to its full potential, supporting HTTP/2, HTTP/3, as well as WebSocket. It's already installed alongside Quart and is very straightforward to use. For our dataservice application, we would run:

$ hypercorn dataservice:app

Hypercorn is the latest in a mine of WSGI and ASGI servers that aim to serve web applications, and if you are searching the Flask documentation when looking...