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Flask Authentication Libraries

Curated list of the most awesome Flask Authentication Libraries .

  • arxiv-auth - Login page and core auth library.
  • authcode - Awesome auth library for Flask and Bottle web apps.
  • pf-flask-auth - Flask Authentication by Problem Fighter Library.
  • propelauth-flask - A Flask library for managing authentication, backed by PropelAuth .
  • Azure-FastAPI-Auth-Example - FastAPI Azure SSO demo. A Python port from the primary Microsoft Flask example to a FastAPI app that uses similar helper functions & the Microsoft MSAL library to authenticate a user via SSO, get the JWT(s), & make an http request to the Graph API on behalf of the user..
  • Flask-authgen-jwt - A flask library in which uses pyjwt to encode and decode JWTs but with the improvements in which you can define user roles to the endpoints so its better to use this library with that extra level of security. Also you can generate a JWT using basic authentication first to retrieve a token with the respective personalizations and then keep using that token. All options of pywjt to generate a token are going to be available..
  • Flask-Auth - Explore flask libraries for account management, authentication, authorization..
  • flask-user-authentication - using flask and sql library.
  • FlaskOAuthServer - Own implementation of an authentication server (OAuth 2.0) with the python library Authlib.
  • Authentication-in-Flask-using-Postgresql - A secure signup-login api written in python using sqlalchemy library.
  • simple_authentication - Flask and Flask-SQLAlchemy, libraries that manages User registration, log in, session, and logout functions, are used in this code example..
  • Flask-Tread - Library for Flask route input and output validation, authentication and transformation.
  • flask-auth - A library for setting up Authentication, Authorization, and Throttling in Flask..
  • Authentication-Flask-React-Docker - Project involving adding user authentication to a Flask and React micro-service using React Testing Library and PyTest to test both apps, Formik to manage form state, and GitHub Actions to deploy Docker images to Heroku..
  • User-role-auth-with-flask - User based role authentication create in Flask framework. All the libraries used are open source. Only the backend code is available..
  • OAuth2-with-MSAL - Integrating the Microsoft Authentication Library, or msal, into a Flask application with Azure Active Directory.
  • flask-aad-auth - This is a simple Flask web application that demonstrates how to authenticate users with Azure Active Directory (AD) and redirect them to a secured page after successful login. The application uses the Microsoft Authentication Library (MSAL) for Python to perform the authentication..
  • login-registration-with-otp - Basic Flask application with user registration, login, and OTP verification functionality, along with API endpoints for authentication. It utilizes various Flask extensions and libraries to handle database operations, form handling, password hashing, email sending, and user authentication..
  • user-api - An experiment with user APIs in Python using the Flask library.
  • RestApiBurger - A simple rest api made in python using flask library. The server requires authentication and it is included by burger's data.
  • AuthFlow - This project involves adding user authentication to a Flask and React microservice using tools such as Formik, React Testing Library, pytest, and GitLab CI..
  • simple_oauth2 - Simple OAuth2 library for Python.
  • oauth2-rfc6749 - Library for RFC6749 (OAuth2); including all that's needed for a frontend REST API wrapper (e.g.: written in Bottle, Flask or Twisted-Matrix) to expose OAuth2 authentication flows for their users..
  • Twitter-Government-Sentiment-Analysis - One of the major projects I have worked on till now outside of curriculum is a Twitter Government Sentiment Analysis. It is not just a regular sentiment analysis from a tweet input but has a lot more functionalities and complexity. To give a brief idea about what it does, the project searches a hashtag and displays real time tweets, the user who tweeted it, total retweet count of that tweet, all the hashtags used in each tweet, and most importantly the sentiment analysis of each tweet (whether it is a positive tweet or negative). The result shows the most recent 200 tweets from the day you want it to be searched from by taking a hashtag and date as input from the user. At the top of the result table, you get the total positive tweets percentage and negative tweets percentage of that hashtag. It is a full-fledged website with attractive frontend and smooth backend developed by me. I have developed the sentiment analysis model using logistic regression algorithm, and sqlite3 for database management. The major libraries I needed in the machine learning part are sklearn for logistic regression, nltk for preprocessing and tweepy for twitter authentication and tweets handling. I used matplotlib and seaborn libraries for result visualization to improve the accuracy of my project. The final accuracy I achieved is 98%. Coming to the website building, I have used Flask as my backend language and HTML, CSS, Javascript for frontend. Using Javascript, I was able to add beautiful scroll-animation effect to my project which gave it a more subtle and pleasing user experience. This project can be very useful for companies wanting to take a quick review on what's being said about their product on social media, especially from a specific period where they have made a significant change in their servicing or any other prospect of their product. They can understand the percentage of people who find their product/service positive or negative within seconds. .