Glossary · Web & App Development
FastAPI
Overview
What FastAPI is and how it works
FastAPI is a Python web framework for building APIs that leans on standard Python type hints to define request and response data. From those hints it automatically validates incoming data, serializes responses, and generates interactive OpenAPI (Swagger) documentation. It is asynchronous by design, built on the Starlette web toolkit and the Pydantic data-validation library.
Why FastAPI is popular
FastAPI delivers performance competitive with Node.js and Go while keeping Python's readability, and its type-driven approach catches errors early and documents the API for free. Those traits have made it a favorite for machine-learning and AI services, where Python models need a fast, well-typed HTTP layer. Strong developer experience and automatic docs speed up delivery.
How an agency uses FastAPI
For backend development, full-stack development, and app backend and API development, FastAPI is a natural fit when the stack is Python or when a project needs to expose AI and data services over an API. Auto-generated documentation makes handoff between backend and frontend teams smoother, which an in-house team uses to keep projects moving without ambiguity.
Where we use it
Related Zen in Tech services
How our team puts FastAPI to work in real projects.
FAQ
FastAPI — common questions
FastAPI vs Django — which should I choose?
Choose FastAPI for high-performance, API-only services, especially async workloads and AI/ML endpoints. Choose Django when you want a full, batteries-included framework with an ORM, admin, and templating for complete web applications. They solve different problems and are sometimes used together.
Is FastAPI production-ready?
Yes. FastAPI is mature, widely used in production at scale, and backed by an active ecosystem. Paired with an ASGI server like Uvicorn or Gunicorn, it handles demanding, high-concurrency workloads reliably.
Is FastAPI good for AI and machine-learning apps?
Very. FastAPI is one of the most common ways to serve Python-based AI and ML models over an API, thanks to its speed, async support, and automatic validation of inputs and outputs.
Need FastAPI done right?
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