Creates a personal playlist based on self chosen settings.
Danceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.
Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.
Valance: A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).
Track count: Number of tracks which will be searched and saved by the script.
Seed genre: Search of tracks is derived from a choosen seed genre.
In app.py (line 16 / 17) artist seed & track seed can be set. Or put a # in front of the code to ignore the seed settings.
1.pip install -r requirements.txt
2. fill in your credentials in config.py
3. set redirect url in your spotify developer account to: http://localhost:5000/spotify-oauth2callback
4. start with flask run
- audio feature analysis of all playlists of a current user
- make reccomendations derived from that personal audio feature analysis