new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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FastAPI · all subjects

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12 notes, read out of this brain and free to use. Each one was extracted from a source and is re-checked against its exam.

FastAPI motivation from Django REST Framework

FastAPI was inspired by Django REST Framework's automatic API documentation web user interface as one of the first ideas that motivated FastAPI's creation.

FastAPI inspiration from Flask microframework design

FastAPI adopted Flask's microframework approach to be simple and flexible, allowing mixing and matching of tools and parts as needed, with a simple routing system.

FastAPI inspired by Requests library design

FastAPI adopted inspiration from the Requests library: a simple and intuitive API with sensible defaults but powerful customization, using HTTP method names directly in a straightforward way.

FastAPI uses OpenAPI standard for API documentation

FastAPI adopted the OpenAPI standard (formerly Swagger version 2.0+) for API specifications and integrates standards-based UI tools including Swagger UI and ReDoc for automatic API documentation.

FastAPI inspired by Marshmallow and Webargs

FastAPI was inspired by Marshmallow (data validation and serialization) and Webargs (parsing incoming request data) to use code to define schemas with data types and validation automatically.

FastAPI dependency injection inspired by NestJS

FastAPI was inspired by NestJS (a TypeScript NodeJS framework) to have a powerful dependency injection system while minimizing code repetition, and to use types for great editor support.

FastAPI performance based on Starlette and Uvicorn

FastAPI achieves high performance by being based on Starlette, which is currently the fastest Python framework tested. Starlette was created after Sanic and uses similar async principles but has surpassed Sanic in open benchmarks.

FastAPI inspired by Hug for type hints in parameters

Hug was one of the first frameworks to implement declaration of API parameter types using Python type hints. This idea inspired FastAPI to use Python type hints to declare parameters and automatically generate API schemas.

FastAPI response parameter inspired by Falcon and Hug

FastAPI was inspired by Falcon and Hug to include an optional response parameter in path operation functions for setting headers, cookies, and alternative status codes.

APIStar was the direct inspiration for FastAPI

FastAPI considers itself a spiritual successor to APIStar (which was shifted from being a web framework to being OpenAPI validation tools). APIStar demonstrated the brilliant idea of declaring multiple things (data validation, serialization, documentation) with the same Python types while providing great editor support. APIStar was created by Tom Christie, who also created Django REST Framework, Starlette, and Uvicorn.

FastAPI inspired by Molten for extra validations

FastAPI was inspired by Molten to define extra validations for data types using the default value of model attributes, which improves editor support. This functionality was later incorporated into Pydantic itself.

FastAPI license

FastAPI is licensed under the MIT license.

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