Fastapi-auth-middleware - Lightweight auth middleware for FastAPI that just works. Fits most auth workflows with only a few lines of code

Overview

FastAPI Auth Middleware

We at Code Specialist love FastAPI for its simplicity and feature-richness. Though we were a bit staggered by the poor documentation and integration of auth-concepts. That's why we wrote a FastAPI Auth Middleware. It integrates seamlessly into FastAPI applications and requires minimum configuration. It is built upon Starlette and thereby requires no dependencies you do not have included anyway.

Caution: This is a middleware to plug in existing authentication. Even though we offer some sample code, this package assumes you already have a way to generate and verify whatever you use, to authenticate your users. In most of the usual cases this will be an access token or bearer. For instance as in OAuth2 or Open ID Connect.

Install

pip install fastapi-auth-middleware

Why FastAPI Auth Middlware?

  • Application or Route scoped automatic authorization and authentication with the perks of dependency injection (But without inflated signatures due to Depends())
  • Lightweight without additional dependencies
  • Easy to configure
  • Easy to extend and adjust to specific needs
  • Plug-and-Play feeling

Usage

The usage of this middleware requires you to provide a single function that validates a given authorization header. The middleware will extract the content of the Authorization HTTP header and inject it into your function that returns a list of scopes and a user object. The list of scopes may be empty if you do not use any scope based concepts. The user object must be a BaseUser or any inheriting class such as FastAPIUser. Thereby, your verify_authorization_header function must implement a signature that contains a string as an input and a Tuple of a List of strings and a BaseUser as output:

from typing import Tuple, List
from fastapi_auth_middleware import FastAPIUser
from starlette.authentication import BaseUser

...
# Takes a string that will look like 'Bearer eyJhbGc...'
def verify_authorization_header(auth_header: str) -> Tuple[List[str], BaseUser]: # Returns a Tuple of a List of scopes (string) and a BaseUser
    user = FastAPIUser(first_name="Code", last_name="Specialist", user_id=1)  # Usually you would decode the JWT here and verify its signature to extract the 'sub'
    scopes = []  # You could for instance use the scopes provided in the JWT or request them by looking up the scopes with the 'sub' somewhere
    return scopes, user

This function is then included as an keyword argument when adding the middleware to the app.

from fastapi import FastAPI
from fastapi_auth_middleware import AuthMiddleware

...

app = FastAPI()
app.add_middleware(AuthMiddleware, verify_authorization_header=verify_authorization_header)

After adding this middleware, all requests will pass the verify_authorization_header function and contain the scopes as well as the user object as injected dependencies. All requests now pass the verify_authorization_header method. You may also verify that users posses scopes with requires:

from starlette.authentication import requires

...

@app.get("/")
@requires(["admin"])  # Will result in an HTTP 401 if the scope is not matched
def some_endpoint():
    ...

You are also able to use the user object you injected on the request object:

from starlette.requests import Request

...

@app.get('/')
def home(request: Request):
    return f"Hello {request.user.first_name}"  # Assuming you use the FastAPIUser object

Examples

Various examples on how to use this middleware are available at https://code-specialist.github.io/fastapi-auth-middleware/examples

Comments
  • tests multiple python versions in test pipeline

    tests multiple python versions in test pipeline

    This PR:

    • runs the test pipeline with all supported python versions instead of only Python 3.8
    • adds a badge for the test status on master to the README
    enhancement 
    opened by JonasScholl 2
  • proper error handling in authentication middleware

    proper error handling in authentication middleware

    When an error in an starlette AuthenticationBackend occurs, a AuthenticationError must be raised, other exceptions may produce errors like: 'RuntimeError: Caught handled exception, but response already started.' (see starlette documentation)

    This PR:

    • catches all exceptions that occur in the verify_authorization_header callback and convert them into an AuthenticationError
    • adds an optional error handler callback for specifically catching auth errors and returning a custom response (since this is already offered by the AuthenticationBackend implentation from starlette)
    • does some type hint improvements, I couldn't resist πŸ˜‚
    opened by JonasScholl 1
  • OAuth2Middleware with automatic renewal added

    OAuth2Middleware with automatic renewal added

    • Async support for the AuthMiddleware
    • OAuth2Middleware added
    • Write tests (100% coverage)
    • Documentation
    • Add example

    TODO before merging:

    • Add example with the fastapi-keycloak package -> Convert to issue #1
    enhancement 
    opened by yannicschroeer 1
  • Integrate with fastapi openapi authentication

    Integrate with fastapi openapi authentication

    Is there a way to make this middleware correctly integrate with the openapi generators from fastapi? For instance. Currently, this:

    @router.get("/me", response_model=schemas.User)
    @requires('user')
    async def read_user_me(request: Request, db: Session = Depends(get_db)):
      user = User.get_user(db, request.user.userid)
      return user
    

    Is not detected by fastapi's openapi generator as an authenticated endpoint. Is there a way to make this library integrate correctly with the openapi generator.

    image

    opened by xtrm0 0
  • Protected and Unprotected Endpoints

    Protected and Unprotected Endpoints

    I'm trying the middleware and reading the docs

    Once Starlette includes this and FastAPI adopts it, there will be a more elegant solution to this.

    FYI https://github.com/encode/starlette/pull/1649

    opened by paolodina 0
Releases(1.0.2)
  • 1.0.2(Apr 7, 2022)

  • 1.0.1(Mar 24, 2022)

    What's Changed

    • Excluded URLs by @yannicschroeer in https://github.com/code-specialist/fastapi-auth-middleware/pull/6

    Full Changelog: https://github.com/code-specialist/fastapi-auth-middleware/compare/1.0.0...1.0.1

    Source code(tar.gz)
    Source code(zip)
  • 1.0.0(Mar 15, 2022)

    What's Changed

    • proper error handling in authentication middleware by @JonasScholl in https://github.com/code-specialist/fastapi-auth-middleware/pull/2
    • OAuth2Middleware with automatic renewal added by @yannicschroeer in https://github.com/code-specialist/fastapi-auth-middleware/pull/1
    • Improved the reusability of the middleware by passing all headers ins… by @yannicschroeer in https://github.com/code-specialist/fastapi-auth-middleware/pull/3

    New Contributors

    • @JonasScholl made their first contribution in https://github.com/code-specialist/fastapi-auth-middleware/pull/2
    • @yannicschroeer made their first contribution in https://github.com/code-specialist/fastapi-auth-middleware/pull/1

    Full Changelog: https://github.com/code-specialist/fastapi-auth-middleware/commits/1.0.0

    Source code(tar.gz)
    Source code(zip)
Owner
Code Specialist
Code Quality Blog about simplifying concepts and making life easier for developers
Code Specialist
flask extension for integration with the awesome pydantic package

flask extension for integration with the awesome pydantic package

249 Jan 06, 2023
Hook Slinger acts as a simple service that lets you send, retry, and manage event-triggered POST requests, aka webhooks

Hook Slinger acts as a simple service that lets you send, retry, and manage event-triggered POST requests, aka webhooks. It provides a fully self-contained docker image that is easy to orchestrate, m

Redowan Delowar 96 Jan 02, 2023
Adds integration of the Chameleon template language to FastAPI.

fastapi-chameleon Adds integration of the Chameleon template language to FastAPI. If you are interested in Jinja instead, see the sister project: gith

Michael Kennedy 124 Nov 26, 2022
Feature rich robust FastAPI template.

Flexible and Lightweight general-purpose template for FastAPI. Usage ⚠️ Git, Python and Poetry must be installed and accessible ⚠️ Poetry version must

Pavel Kirilin 588 Jan 04, 2023
Easy and secure implementation of Azure AD for your FastAPI APIs πŸ”’

FastAPI-Azure-auth Azure AD Authentication for FastAPI apps made easy. πŸš€ Description FastAPI is a modern, fast (high-performance), web framework for

Intility 216 Dec 27, 2022
Sample FastAPI project that uses async SQLAlchemy, SQLModel, Postgres, Alembic, and Docker.

FastAPI + SQLModel + Alembic Sample FastAPI project that uses async SQLAlchemy, SQLModel, Postgres, Alembic, and Docker. Want to learn how to build th

228 Jan 02, 2023
fastapi-cache is a tool to cache fastapi response and function result, with backends support redis and memcached.

fastapi-cache Introduction fastapi-cache is a tool to cache fastapi response and function result, with backends support redis, memcache, and dynamodb.

long2ice 551 Jan 08, 2023
Cache-house - Caching tool for python, working with Redis single instance and Redis cluster mode

Caching tool for python, working with Redis single instance and Redis cluster mo

Tural 14 Jan 06, 2022
Single Page App with Flask and Vue.js

Developing a Single Page App with FastAPI and Vue.js Want to learn how to build this? Check out the post. Want to use this project? Build the images a

91 Jan 05, 2023
Restful Api developed with Flask using Prometheus and Grafana for monitoring and containerization with Docker :rocket:

Hephaestus πŸš€ In Greek mythology, Hephaestus was either the son of Zeus and Hera or he was Hera's parthenogenous child. ... As a smithing god, Hephaes

Yasser Tahiri 16 Oct 07, 2022
OpenAPI for Todolist RESTful API

swagger-client OpenAPI for Todolist RESTful API This Python package is automatically generated by the Swagger Codegen project: API version: 1 Package

Iko Afianando 1 Dec 19, 2021
FastAPI client generator

FastAPI-based API Client Generator Generate a mypy- and IDE-friendly API client from an OpenAPI spec. Sync and async interfaces are both available Com

David Montague 283 Jan 04, 2023
FastAPI CRUD template using Deta Base

Deta Base FastAPI CRUD FastAPI CRUD template using Deta Base Setup Install the requirements for the CRUD: pip3 install -r requirements.txt Add your D

Sebastian Ponce 2 Dec 15, 2021
A rate limiter for Starlette and FastAPI

SlowApi A rate limiting library for Starlette and FastAPI adapted from flask-limiter. Note: this is alpha quality code still, the API may change, and

Laurent Savaete 562 Jan 01, 2023
Starlette middleware for Prerender

Prerender Python Starlette Starlette middleware for Prerender Documentation: https://BeeMyDesk.github.io/prerender-python-starlette/ Source Code: http

BeeMyDesk 14 May 02, 2021
Qwerkey is a social media platform for connecting and learning more about mechanical keyboards built on React and Redux in the frontend and Flask in the backend on top of a PostgreSQL database.

Flask React Project This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github

Peter Mai 22 Dec 20, 2022
Basic fastapi blockchain - An api based blockchain with full functionality

Basic fastapi blockchain - An api based blockchain with full functionality

1 Nov 27, 2021
A RESTful API for creating and monitoring resource components of a hypothetical build system. Built with FastAPI and pydantic. Complete with testing and CI.

diskspace-monitor-CRUD Background The build system is part of a large environment with a multitude of different components. Many of the components hav

Nick Hopewell 67 Dec 14, 2022
Simple example of FastAPI + Celery + Triton for benchmarking

You can see the previous work from: https://github.com/Curt-Park/producer-consumer-fastapi-celery https://github.com/Curt-Park/triton-inference-server

Jinwoo Park (Curt) 37 Dec 29, 2022
A set of demo of deploying a Machine Learning Model in production using various methods

Machine Learning Model in Production This git is for those who have concern about serving your machine learning model to production. Overview The tuto

Vo Van Tu 53 Sep 14, 2022