电子书百科大全
Python Microservices with FastAPI: Design production-ready, AI-enabled microservices with Python
Author(s): Giunio De Luca (Author), Igor Benav (Author)
- Publisher: Packt Publishing - ebooks Account
- Publication Date: January 11, 2027
- Language: English
- Print length: 355 pages
- ISBN-10: 1835461166
- ISBN-13: 9781835461167
Book Description
Design and ship production-ready FastAPI microservices from first service to secure authentication, bookings, reviews, smart search, AI-assisted support, reliable testing, and a confident path to scalable production systems
Key Features
- Design clear, evolvable services, and explain decisions your team trusts
- Ship reliable backends with the right data stores, async jobs, auth, testing, and observability
- Add practical AI features (RAG, agents) that reduces support and drives measurable value
Book Description
This book shows you how to turn an idea into a reliable product.
This is a playbook for practical progress. Choose what to ship now, what to delay, and how to avoid risky changes. Keep services tidy, naming clear, and tests small but useful. You will build a realistic end-to-end system step by step, following the evolution of a babysitting marketplace platform with sign-up, search, booking, messaging, and payments delivered in steady increments.
When it is time to add intelligence, you learn practical ways to use AI for customer support, recommendations, and operational insights. The focus stays on measurable value, not hype, while keeping performance, costs, and reliability predictable in production.
Your guides are Giunio De Luca, PhD, author of Packt’s FastAPI Cookbook and an architect who has shipped systems across research, sports, and energy, and Igor “Benav” Magalhães, founder of Benav Labs and maintainer of widely used open-source tools. They share patterns they rely on when deadlines are real and reliability matters.
By the end, you will not just know FastAPI. You will think like a senior engineer, plan delivery with confidence, avoid common traps, measure what matters, and run a backend platform that users trust and teams enjoy maintaining.
What you will learn
- Set up a microservice from scratch with modern Python tooling
- Build RESTful APIs with clean boundaries, DI, and type-safe models
- Design multiple services and compose them through a gateway
- Model data with PostgreSQL, MongoDB, and vector stores
- Scale with async I/O, background tasks, queues, and WebSockets
- Secure services with OAuth2/JWT and role-based access
- Test, profile, observe, and deploy with confidence
- Add AI features including RAG chatbots, agents, and analytics
Who this book is for
For Python developers who want to move beyond monoliths and ship scalable backends. Ideal for engineers aiming for lead/architect roles who need practical patterns for clean code, async workflows, and multi-database design. You’ll learn how to add secure authentication, real-time features, and AI capabilities RAG chat, agents, and analytics without losing testability or performance. Basic Python and web API knowledge is recommended.
Table of Contents
- Kickstarting the Platform: Project Setup and First FastAPI Endpoint
- Creating the buyer portal: Endpoints, State and Cookies
- Designing the Seller Portal: Clean Architecture and Middleware
- Managing User Requests: Dependency Injection in Practice
- Connecting Buyers and Sellers: Building Microservices
- User Registration System: SQL Databases with SQLAlchemy
- Managing the Car Catalogue: MongoDB and Document Databases
- Scheduling Appointments: Authentication, OAuth2, and JWT
- Handling Complaints: Asynchronous Tasks and WebSockets
- Building a Customer Support Chatbot with Generative AI
- Analytics Portal: Exploring Business Intelligence with AI
- Optimizing for High Traffic: Performance, Profiling, and Production
Editorial Reviews
About the Author
Giunio De Luca is a software engineer with over 10 years of experience in fields such as physics, sports, and administration. He graduated in industrial engineering from the University of Basilicata and holds a PhD in numerical simulations from Paris-Saclay University. His work spans developing advanced algorithms, creating sports analytics applications, and improving administrative processes. As an independent consultant, he collaborates with research labs, government agencies, and start-ups across Europe. He also supports coding education in schools and universities through workshops, lectures, and mentorship programs, inspiring the next generation of software engineers with his expertise and dedication.
Igor “Benav” Magalhães Software engineer and entrepreneur in Brazil, founder of Benav Labs. Studied Applied Mathematics at UFRJ; maintains popular open-source projects such as FastCRUD. Builds production systems with FastAPI and PydanticAI, data stacks with Snowflake and dbt, and specializes in multi-agent AI systems.
{"@context":"https://schema.org","@type":"Book","name":"Python Microservices with FastAPI: Design production-ready, AI-enabled microservices with Python","image":"https://m.media-amazon.com/images/I/41h4yosfE6L._SY342_.jpg","author":{"@type":"Person","name":"Giunio De Luca (Author), Igor Benav (Author)"},"publisher":{"@type":"Organization","name":"Packt Publishing - ebooks Account"},"datePublished":"January 11, 2027","isbn":"9781835461167","numberOfPages":355,"inLanguage":"English","description":"Design and ship production-ready FastAPI microservices from first service to secure authentication, bookings, reviews, smart search, AI-assisted support, reliable testing, and a confident path to scalable production systemsKey FeaturesDesign clear, evolvable services, and explain decisions your team trustsShip reliable backends with the right data stores, async jobs, auth, testing, and observabilityAdd practical AI features (RAG, agents) that reduces support and drives measurable valueBook DescriptionThis book shows you how to turn an idea into a reliable product.This is a playbook for practical progress. Choose what to ship now, what to delay, and how to avoid risky changes. Keep services tidy, naming clear, and tests small but useful. You will build a realistic end-to-end system step by step, following the evolution of a babysitting marketplace platform with sign-up, search, booking, messaging, and payments delivered in steady increments.When it is time to add intelligence, you learn practical ways to use AI for customer support, recommendations, and operational insights. The focus stays on measurable value, not hype, while keeping performance, costs, and reliability predictable in production.Your guides are Giunio De Luca, PhD, author of Packt’s FastAPI Cookbook and an architect who has shipped systems across research, sports, and energy, and Igor “Benav” Magalhães, founder of Benav Labs and maintainer of widely used open-source tools. They share patterns they rely on when deadlines are real and reliability matters.By the end, you will not just know FastAPI. You will think like a senior engineer, plan delivery with confidence, avoid common traps, measure what matters, and run a backend platform that users trust and teams enjoy maintaining.What you will learnSet up a microservice from scratch with modern Python toolingBuild RESTful APIs with clean boundaries, DI, and type-safe modelsDesign multiple services and compose them through a gatewayModel data with PostgreSQL, MongoDB, and vector storesScale with async I/O, background tasks, queues, and WebSocketsSecure services with OAuth2/JWT and role-based accessTest, profile, observe, and deploy with confidenceAdd AI features including RAG chatbots, agents, and analyticsWho this book is forFor Python developers who want to move beyond monoliths and ship scalable backends. Ideal for engineers aiming for lead/architect roles who need practical patterns for clean code, async workflows, and multi-database design. You’ll learn how to add secure authentication, real-time features, and AI capabilities RAG chat, agents, and analytics without losing testability or performance. Basic Python and web API knowledge is recommended.Table of ContentsKickstarting the Platform: Project Setup and First FastAPI EndpointCreating the buyer portal: Endpoints, State and CookiesDesigning the Seller Portal: Clean Architecture and MiddlewareManaging User Requests: Dependency Injection in PracticeConnecting Buyers and Sellers: Building MicroservicesUser Registration System: SQL Databases with SQLAlchemyManaging the Car Catalogue: MongoDB and Document DatabasesScheduling Appointments: Authentication, OAuth2, and JWTHandling Complaints: Asynchronous Tasks and WebSocketsBuilding a Customer Support Chatbot with Generative AIAnalytics Portal: Exploring Business Intelligence with AIOptimizing for High Traffic: Performance, Profiling, and Production","url":"https://www.amazon.com/dp/1835461166/","bookFormat":"http://schema.org/EBook","additionalType":"http://schema.org/PDF","fileSize":"66 MB","accessibilityFeature":["login required","member access only"],"accessibilitySummary":"PDF version available to authenticated members only. File size: 66 MB."}
评论前必须登录！
立即登录 注册