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Third Party Packages

Starlette has a rapidly growing community of developers, building tools that integrate into Starlette, tools that depend on Starlette, etc.

Here are some of those third party packages:


Starlette APISpec


Easy APISpec integration for Starlette.

Document your REST API built with Starlette by declaring OpenAPI (Swagger) schemas in YAML format in your endpoints' docstrings.

Starlette API


That library aims to bring a layer on top of Starlette framework to provide useful mechanism for building APIs. It's based on API Star, inheriting some nice ideas like:

  • Schema system based on Marshmallow that allows to declare the inputs and outputs of endpoints and provides a reliable way of validate data against those schemas.
  • Dependency Injection that ease the process of managing parameters needed in endpoints.
  • Components as the base of the plugin ecosystem, allowing you to create custom or use those already defined in your endpoints, injected as parameters.
  • Starlette ASGI objects like Request, Response, Session and so on are defined as components and ready to be injected in your endpoints.



Declarative request parsing and validation for Starlette, built on top of webargs.

Allows you to parse querystring, JSON, form, headers, and cookies using type annotations.

import uvicorn
from starlette.applications import Starlette
from starlette.responses import JSONResponse
from webargs_starlette import use_annotations

app = Starlette()

async def index(request, name: str = "World"):
    return JSONResponse({"Hello": name})

if __name__ == "__main__":, port=5000)

# curl 'http://localhost:5000/'
# {"Hello": "World"}
# curl 'http://localhost:5000/?name=Ada'
# {"Hello": "Ada"}




A familiar HTTP Service Framework for Python.

  • Flask-style route expression, with new capabilities -- all while using Python 3.6+'s new f-string syntax.
  • Falcon's "every request and response is passed into to each view and mutated" methodology.
  • Support for YAML by default.
  • Several of Starlette's optional dependencies pre-installed, like:
    • Production static file server.
    • Uvicorn server.
    • GraphQL support, via Graphene.
import responder

api = responder.API()

async def greet_world(req, resp, *, greeting):
    resp.text = f"{greeting}, world!"

if __name__ == '__main__':



High performance, easy to learn, fast to code, ready for production.

An API framework inspired by APIStar's previous server system with type declarations for route parameters, based on the OpenAPI specification version 3.0.0+ (with JSON Schema), powered by Pydantic for the data handling.

Use standard Python 3.6+ types as parameters to get:

  • Autocomplete everywhere.
  • Data conversion.
  • Data validation.
  • Automatic documentation with OpenAPI (and JSON Schema), based on the same Python types.


  • A simple but powerful dependency injection system.
  • Automatic interactive documentation (based on Swagger UI and ReDoc).
  • Security utilities, including OAuth2 with JWT tokens.
from fastapi import FastAPI

app = FastAPI()

def read_root():
    return {'hello': 'world'}