FastOpenAPI has emerged as a solution for developers who appreciate FastAPI's intuitive approach to API documentation but need to work with different Python web frameworks. This library bridges a significant gap in the Python web ecosystem by bringing consistent OpenAPI schema generation across multiple frameworks including Flask, Falcon, Sanic, Starlette, and Tornado.
Supported Frameworks
- Falcon
- Flask
- Quart
- Sanic
- Starlette
- Tornado
Key Features
- Generate OpenAPI schemas with Pydantic v2
- Data validation using Pydantic models
- Proxy routing provides FastAPI-style routing
- Support for Swagger UI and ReDoc documentation interfaces
Code-First vs. Spec-First API Development
The community discussion around FastOpenAPI has reignited the debate between code-first and spec-first API development approaches. Code-first development, as exemplified by FastAPI and now FastOpenAPI, allows developers to define their API directly in code with decorators and type annotations. This approach tends to be more intuitive for Python developers and aligns well with Python's dynamic nature.
In contrast, spec-first development involves creating an OpenAPI specification document first, then implementing the API based on that specification. While this approach requires more upfront work, it offers advantages for larger teams and public APIs.
Spec-first is my preferred approach these days, but I had to grow into it. It didn't make sense early on until I'd written the same boilerplate 100s of times and realised how much time I was wasting. The upfront cost is higher than the 10 lines it takes to make a working FastAPI app, but once you're past that it becomes a huge timesaver.
Many developers noted that spec-first becomes particularly valuable in collaborative environments where APIs need to be designed and reviewed before implementation, while code-first excels in rapid development scenarios and private APIs where individual developer velocity is prioritized.
Framework Flexibility Without Sacrificing Documentation
A key benefit highlighted by community members is the ability to maintain existing codebases while gaining FastAPI-style documentation. Several commenters mentioned working with legacy Flask applications alongside newer FastAPI services, creating a need for consistent documentation across different frameworks.
FastOpenAPI addresses this by providing a unified approach to route definition and documentation that works across multiple frameworks. This is particularly valuable for organizations that can't easily migrate all their services to a single framework but want consistent API documentation.
The implementation is described as seamless by users, requiring minimal changes to existing code structure while providing substantial benefits in terms of documentation, validation, and developer experience.
Python Async Ecosystem Challenges
The discussion also touched on broader challenges within Python's asynchronous programming ecosystem. Some developers expressed frustration with the split in the Python ecosystem between synchronous and asynchronous code, noting debugging difficulties and compatibility issues.
FastOpenAPI's support for both traditional synchronous frameworks like Flask and asynchronous ones like Sanic and Starlette reflects the current state of Python web development, where both paradigms coexist and are chosen based on specific project requirements.
Several commenters debated the merits of Python's asyncio implementation compared to alternatives like Gevent, highlighting ongoing tensions in how Python handles concurrency. FastOpenAPI sidesteps this debate by supporting multiple frameworks regardless of their concurrency model.
Framework Support and Future Development
While FastOpenAPI currently supports six Python frameworks (Falcon, Flask, Quart, Sanic, Starlette, and Tornado), community members inquired about additional framework support, particularly for Django. The developer indicated that Django integration is on the roadmap but presents unique challenges due to its project structure.
The community also discussed potential features like automatic response model inference from return types, which would further reduce boilerplate code. The developer expressed openness to adding such features in future updates.
FastOpenAPI represents an interesting evolution in the Python web ecosystem, bringing the developer-friendly aspects of FastAPI to a broader range of frameworks. As web APIs continue to proliferate, tools that simplify documentation and standardize development patterns across frameworks fill an important need for development teams working with diverse technology stacks.
Reference: FastOpenAPI