Spotify API: Fetching Artist Details like Popularity, Followers, Top Tracks, and its Details
In a fast digital music situation, personalized recommendations play a --key role in improving user experience and satisfaction. This paper examines the development of a personalized music discovery system. This is used by the Spotify -Web -API to interact with user preferences and provide tailor-made content. The system has features such as searching for artists, related artists, related artists covered, persecution of choices based on user input, and pagination of music. The system can invoke detailed information about artists, tracks, and albums, allowing users to explore top tracks based on their preferences, such as tracks, market regions, and more. This paper describes the design, architecture, and implementation of the system, followed by evaluations of its performance and user friendlyness.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-10
- DOI
- https://doi.org/10.5281/zenodo.14998644
- Primary Topic
- Computational Physics and Python Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00