May 1, 2024
Updated June 18, 2025
16 minute read
FastAPI: A Modern Framework for High-Performance APIs
FastAPI has rapidly emerged as a popular, high-performance web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to code, and to produce highly performant applications. For developers looking to build robust and efficient web services, understanding FastAPI can be a significant asset.
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Find a path to becoming a FastAPI. Learn more at:
OpenCourser.com/topic/4adqw9/fastap
Reading list
We've selected 21 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
FastAPI.
Is specifically tailored for data scientists and developers interested in using FastAPI to build and deploy machine learning applications. It covers integrating ML models, dependency injection, authentication, testing, and deployment best practices within the context of data science.
Focuses on using FastAPI for building secure, scalable, and structured Python microservices. It covers microservices design patterns, asynchronous and synchronous REST services, event-driven applications, and integrating with databases in a microservices architecture.
This practical guide focuses on building production-grade AI services using FastAPI, specifically integrating large language models (LLMs). It covers setting up FastAPI applications for AI, integrating with tools like Ollama, asynchronous processing for AI workloads, database operations, authentication, and deployment using Docker.
Offers a practical guide to building production-ready web APIs with FastAPI, focusing on core concepts like routing, request handling, and error handling. It covers integrating with SQL and NoSQL databases, securing applications, and deployment. It's a good resource for Python developers looking to pragmatically learn FastAPI for building robust APIs.
Provides a broad introduction to FastAPI, covering the core concepts and nuts and bolts of development. It's suitable for developers familiar with Python and helps solidify understanding of how FastAPI utilizes modern Python features like type hints and async functions. It also covers RESTful APIs, data validation, authorization, and performance.
This handbook provides a comprehensive and accessible guide to FastAPI, suitable for both novice and experienced developers. It covers foundational to advanced concepts, including dependency injection, CRUD operations, authentication, and deployment strategies, with a focus on practical insights and hands-on experience.
This cookbook offers practical recipes for building high-performance APIs and web applications with FastAPI. It covers a range of topics from basic setup to advanced features like custom middleware, WebSocket communication, and integration with Python libraries. It's a useful reference for tackling specific tasks and exploring advanced techniques.
Guide to using FastAPI to build microservices.
Guide to using FastAPI to build data science APIs.
Guide to using FastAPI to build deep learning APIs.
Delves into the asynchronous nature of FastAPI and its performance benefits compared to WSGI-based frameworks. It provides a comprehensive explanation of using Pydantic models and covers asynchronous interaction with databases, template engines, and deployment options.
While not solely focused on FastAPI, this book covers building microservice APIs with Python using various frameworks, including FastAPI. It delves into service implementation patterns, testing, authentication, authorization, and deployment in cloud environments. It's valuable for understanding the broader context of microservices with FastAPI.
A concise guide aimed at experienced software engineers who need to quickly get up to speed with FastAPI. It likely focuses on the key features and best practices for building applications efficiently. (Based on title and common book patterns for 'busy' professionals)
Covers building full-stack web applications using the FARM stack, which includes FastAPI for the backend. It's useful for developers who want to learn how to integrate FastAPI with frontend technologies and databases to build complete applications.
Is an in-depth guide to writing effective Python code and covers advanced topics relevant to FastAPI development, such as data structures, functions as objects, and concurrency. It's a valuable resource for deepening Python knowledge, which directly impacts FastAPI development.
While not a FastAPI book, this book by one of the authors of a key FastAPI resource provides a strong foundation in modern Python. Understanding concepts like type hints and asynchronous programming from this book would be beneficial before diving into FastAPI.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/4adqw9/fastap
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