LinkBite is a fast, minimalist URL shortener web app built for simplicity. It uses the secrets standard library for PRNG-based cryptographic tokens in Python (see PEP 506 for more info).

LinkBite has a FastAPI + SQLite backend with SQLAlchemy ORM to connect the RESTful API endpoints to the database, and a Gradio frontend. This project also serves as a primer to FastAPI and its advanced functionalities.

• Create and manage your own shortened URLs
• Graceful forwarding: check if the URL exists
• Analytics: count the number of clicks on your URL
• Admin to deactivate shortened links (through a secret key to said links)

It is recommended to install LinkBite within a Python virtual environment. LinkBite has a minimal number of dependencies enlisted in requirements.txt. To install all of them, clone the repository and run

pip install -r requirements.txt

LinkBite uses python-dotenv to build environment variables. To test your build, set your environment variables in a .env file in the install directory.

ENV_NAME="dev"
BASE_URL="http://localhost:8000"
DB_URL="sqlite:///./shortener.db"

FastAPI leverages the ASGI standard to implement asynchronous event loops within a single process. For the web server; in the current directory, run

uvicorn shortener.main:app --reload

You can view all the API endpoints in FastAPI's autogenerated documentation at the base URL, i.e., https://localhost/8000/docs by default, or the alternative documentation at https://localhost/8000/redoc. The API methods have been defined in shortener/main.py.

The tests are for the API endpoints currently and do not test Sessions' database operations. They are written with starlette.testclient and pytest located at shortener/test_main.py. To run the tests, start the server and simply run pytest.

LinkBite has a Gradio frontend connecting to the API endpoints with thin wrappers, inside gradio-app.py. The frontend can be run using

python gradio-app.py

or in reload mode using

gradio gradio-app.py

and then go to https://localhost:7860.

Improvements to the source code, documentation, feature requests, adding and improving tests, and catching and fixing bugs are all welcomed and appreciated – thanks! Please have a look at the issues or the source code.

MIT

@software{Abid_Gradio_Hassle-free_sharing_2019,
author = {Abid, Abubakar and Abdalla, Ali and Abid, Ali and Khan, Dawood and Alfozan, Abdulrahman and Zou, James},
doi = {10.48550/arXiv.1906.02569},
month = {6},
title = {{Gradio: Hassle-free sharing and testing of ML models in the wild}},
url = {https://arxiv.org/abs/1906.02569},
year = {2019}
}