Practical Python Backend Programming, Second Edition: Hands-on backend development with FastAPI, MongoDB, Docker, Kubernetes, and message brokers using Python 3.14 - Softcover

Peters, Tim

9789349174474: Practical Python Backend Programming, Second Edition: Hands-on backend development with FastAPI, MongoDB, Docker, Kubernetes, and message brokers using Python 3.14

Softcover

ISBN 10: 9349174472 ISBN 13: 9789349174474

Publisher: GitforGits, 2026

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All your apps are running on backend systems, and Python gives you one of the best stacks out there for building them.

This edition has been fully revised for Python 3.14, and it puts FastAPI at the centre, with a single real project (a University API) growing across every chapter. It'll be great to use Pydantic to design typed endpoints, work with PostgreSQL and MongoDB through modern async drivers, write concurrent code with structured concurrency, secure your services with PyJWT and OAuth2, and ship everything through Docker, Kubernetes, and CI/CD pipelines. After that, you'll get into microservices, AWS Lambda, gRPC, and message brokers like Kafka and RabbitMQ.

This book is a practical guide for you, not an exhaustive mastery manual. It'll give you the skills you need to get the job done, with all the knowledge you can use straight away. You won't get lost in the details, but the theory will be there when you need it. If you want to build, deploy, and operate Python backends with confidence, this is the place to start.

Key Learnings

Build typed, self-documenting REST APIs with FastAPI, Pydantic, and modern Python type hints.
Structure growing services with routers, dependency injection, settings, and lifespan-managed resources.
Model data in PostgreSQL and MongoDB using SQLAlchemy 2.0 and PyMongo async.
Write concurrent backends with asyncio, TaskGroup, timeouts, and async database access.
Secure applications using PyJWT, OAuth2, role-based access control, and two-factor authentication.
Containerize and deploy services with Docker, Kubernetes, Nginx, and HTTPS.
Automate testing and delivery through pytest and GitHub Actions pipelines.
Decompose monoliths into microservices communicating over REST and gRPC.
Run serverless workloads on AWS Lambda using the Python 3.14 runtime.
Process events and background work with Kafka, Celery, and RabbitMQ.