FastOpenAPI: Generate OpenAPI Schemas for Any Python Framework

Developing APIs is a crucial part of modern software projects, and OpenAPI is the de facto standard for documenting APIs. While FastAPI seamlessly integrates OpenAPI schema generation and documentation, what if you prefer using frameworks like Flask, Falcon, Sanic, or others? FastOpenAPI addresses exactly this need. What is FastOpenAPI? FastOpenAPI is a Python library inspired by FastAPI and built upon Pydantic v2, designed to simplify the generation and integration of OpenAPI schemas with virtually any popular Python framework. Importantly, FastOpenAPI uses "proxy routing": you write routes in a FastAPI-like style, and FastOpenAPI automatically registers them with your chosen framework. Key Features: Support for Falcon, Flask, Quart, Sanic, Starlette, Tornado. Proxy routing with automatic registration. Convenient FastAPI-style API. Automatic documentation generation (Swagger UI, ReDoc). Strong data validation and typing via Pydantic v2. How it Works FastOpenAPI employs a system of adapters (routers), each integrating with a specific framework: BaseRouter: Contains shared logic for schema and documentation generation. Specialized routers (FlaskRouter, SanicRouter, etc.) extend BaseRouter. Minimal Flask API Example: from flask import Flask from pydantic import BaseModel from fastopenapi.routers import FlaskRouter app = Flask(name) router = FlaskRouter(app) class UserResponse(BaseModel): username: str @router.get("/user", tags=["User"], response_model=UserResponse) def get_user(username: str): return UserResponse(username=username) if name == "main": app.run(port=8000) Go to http://localhost:8000/docs to see swagger for example. You can try it: Router Composition FastOpenAPI supports convenient API structuring through router composition, similar to APIRouter in FastAPI. For example, creating versioned APIs: from flask import Flask from pydantic import BaseModel from fastopenapi.routers import FlaskRouter app = Flask(name) main_router = FlaskRouter(app) api_v1 = FlaskRouter() api_v2 = FlaskRouter() class UserResponse(BaseModel): username: str version: str class UserResponseV2(BaseModel): login: str version: str @api_v1.get("/items", tags=["Users", "v1"], response_model=UserResponse) def items_v1(name: str): return UserResponse(username=name, version="1.0") @api_v2.get("/items", tags=["Users", "v2"], response_model=UserResponseV2) def items_v2(name): return UserResponseV2(login=name, version="2.0") main_router.include_router(api_v1, prefix="/api/v1") main_router.include_router(api_v2, prefix="/api/v2") if name == "main": app.run(port=8000) Go to http://localhost:8000/docs: If you prefer ReDoc, you can go to http://localhost:8000/redoc: Generated Documentation Once the server is running, documentation is automatically available: Swagger UI: http://localhost:8000/docs ReDoc: http://localhost:8000/redoc OpenAPI JSON: http://localhost:8000/openapi.json Performance Considerations The project's repository includes basic benchmarks showing that FastOpenAPI introduces only a modest overhead (approximately 2-5%), which is a small price to pay for robust data validation and automatic documentation. Who Should Use FastOpenAPI? Developers wanting OpenAPI support without migrating from their preferred framework. Teams using multiple frameworks seeking standardized API documentation. Installation and Usage # Choose installation based on your preferred framework pip install fastopenapi[falcon] pip install fastopenapi[flask] pip install fastopenapi[sanic] pip install fastopenapi[starlette] pip install fastopenapi[tornado] Conclusion FastOpenAPI is an open-source library that simplifies the addition of OpenAPI specifications to existing Python projects across various frameworks, offering a balance of convenience, flexibility, and performance. Project Repository: mr-fatalyst / fastopenapi FastOpenAPI is a library for generating and integrating OpenAPI schemas using Pydantic v2 and various frameworks (Falcon, Flask, Sanic, Starlette, Tornado). FastOpenAPI is a library for generating and integrating OpenAPI schemas using Pydantic and various frameworks This project was inspired by FastAPI and aims to provide a similar developer-friendly experience

Mar 22, 2025 - 12:29

FastOpenAPI: Generate OpenAPI Schemas for Any Python Framework

Developing APIs is a crucial part of modern software projects, and OpenAPI is the de facto standard for documenting APIs. While FastAPI seamlessly integrates OpenAPI schema generation and documentation, what if you prefer using frameworks like Flask, Falcon, Sanic, or others? FastOpenAPI addresses exactly this need.

What is FastOpenAPI?

FastOpenAPI is a Python library inspired by FastAPI and built upon Pydantic v2, designed to simplify the generation and integration of OpenAPI schemas with virtually any popular Python framework. Importantly, FastOpenAPI uses "proxy routing": you write routes in a FastAPI-like style, and FastOpenAPI automatically registers them with your chosen framework.

Key Features:

Support for Falcon, Flask, Quart, Sanic, Starlette, Tornado.
Proxy routing with automatic registration.
Convenient FastAPI-style API.
Automatic documentation generation (Swagger UI, ReDoc).
Strong data validation and typing via Pydantic v2.

How it Works

FastOpenAPI employs a system of adapters (routers), each integrating with a specific framework:

BaseRouter: Contains shared logic for schema and documentation generation.
Specialized routers (FlaskRouter, SanicRouter, etc.) extend BaseRouter.

Minimal Flask API Example:

from flask import Flask
from pydantic import BaseModel

from fastopenapi.routers import FlaskRouter

app = Flask(__name__)
router = FlaskRouter(app)

class UserResponse(BaseModel):
    username: str

@router.get("/user", tags=["User"], response_model=UserResponse)
def get_user(username: str):
    return UserResponse(username=username)

if __name__ == "__main__":
    app.run(port=8000)

Go to http://localhost:8000/docs to see swagger for example.

You can try it:

Router Composition

FastOpenAPI supports convenient API structuring through router composition, similar to APIRouter in FastAPI. For example, creating versioned APIs:

from flask import Flask
from pydantic import BaseModel

from fastopenapi.routers import FlaskRouter


app = Flask(__name__)
main_router = FlaskRouter(app)

api_v1 = FlaskRouter()
api_v2 = FlaskRouter()

class UserResponse(BaseModel):
    username: str
    version: str

class UserResponseV2(BaseModel):
    login: str
    version: str

@api_v1.get("/items", tags=["Users", "v1"], response_model=UserResponse)
def items_v1(name: str):
    return UserResponse(username=name, version="1.0")

@api_v2.get("/items", tags=["Users", "v2"], response_model=UserResponseV2)
def items_v2(name):
    return UserResponseV2(login=name, version="2.0")

main_router.include_router(api_v1, prefix="/api/v1")
main_router.include_router(api_v2, prefix="/api/v2")

if __name__ == "__main__":
    app.run(port=8000)

Go to http://localhost:8000/docs:

If you prefer ReDoc, you can go to http://localhost:8000/redoc:

Generated Documentation

Once the server is running, documentation is automatically available:

Swagger UI: http://localhost:8000/docs
ReDoc: http://localhost:8000/redoc
OpenAPI JSON: http://localhost:8000/openapi.json

Performance Considerations

The project's repository includes basic benchmarks showing that FastOpenAPI introduces only a modest overhead (approximately 2-5%), which is a small price to pay for robust data validation and automatic documentation.

Who Should Use FastOpenAPI?

Developers wanting OpenAPI support without migrating from their preferred framework.
Teams using multiple frameworks seeking standardized API documentation.

Installation and Usage

# Choose installation based on your preferred framework pip install fastopenapi[falcon] pip install fastopenapi[flask] pip install fastopenapi[sanic] pip install fastopenapi[starlette] pip install fastopenapi[tornado]

Conclusion

FastOpenAPI is an open-source library that simplifies the addition of OpenAPI specifications to existing Python projects across various frameworks, offering a balance of convenience, flexibility, and performance.

Project Repository: