FastAPI Challenge
FastAPI in a Docker container made to update user's listens and recommend him artists.
Project overview Link to heading
Web application that utilizes the power of Python and the FastAPI framework. The application is deployed in a Docker container, ensuring optimal performance and scalability. The application features three distinct endpoints, each providing valuable functionality for the users.
The first endpoint allows users to get the number of times they have listened to a specific artist. It requires user_id as input and returns the number of listens.
The second endpoint allows users to update the number of listens for a specific artist. It requires user_id and the artist’s name, then it updates the number of listens.
The third endpoint allows each user to get personalized recommendations, including a random sample of 5 artists, artists that have never been listened to and artists that are similar to the ones already listened to.
This project demonstrates the power and flexibility of modern web development technologies and their potential to create highly interactive and user-friendly applications in various fields, such as music, entertainment and more.
Tools used
- Python
- Pandas
- FastAPI
- Docker
- GIT
- Github