get-discover-weekly

I was frustrated with having to listen to my Discover Weekly and Release Radar playlists every week to find good new music; I wish there was a way I could more easily sift through my music recommendations.

This is a command line tool that grabs the discover weekly and/or release radar playlist from a Spotify account and reports the most 'danceable' and 'most popular' song. It also saves a .csv file with all the song data from those playlists. Data include name, artists, duration, popularity, tempo, speechiness, acousticness, instrumentalness, danceability, loudness, valence, energy, time signature, liveness, mode, key, explicit, and release date. Look here for an explanation of the audio features, i.e. valence, energy, acousticness, danceability, etc.

This program requires the spotipy Python library (as well as Numpy and Pandas), which can be installed using pip.

Further work could include

• building the package into pip so that its installed in a user and platform-agnostic location
• incorporating other recommendation engines, audio analyses

Installation:

This program requires a Spotify developer / application client id and secret, which can be created here by clicking 'create a client id' then copyubg the client ID and client secret to the declarations in the user_details.py file or adding them as environment variables by writing ~/.zshrc or ~/.bashrc file

export SPOTIFY_CLIENT='client id here'

export SPOTIFY_SECRET='secret here'

and then sourcing the rc file with source ~/.zshrc in terminal.

To make the code work to save the .csv files, edit the line in get_discover_weekly.py that says d.to_csv('~/Desktop/Data_Science/SPOTIPY/playlists_data/%s_playlist_song_data.csv' %(playlist_name),encoding ='utf-8'). Change the path to a location to save your data.

Further tips:

To set up an alias to run this script directly from the command line without having to navigate to the python executable path every time, replace ~/Desktop/Data_Science/SPOTIPY/gdw/ with the directory where the .py files are stored, and add these lines below to ~/.zprofile or ~/.bash_profile (depending on which shell you're using). Then run source ~/.zprofile to source the changes.

alias gdw="python ~/Desktop/Data_Science/SPOTIPY/gdw/get_discover_weekly.py --dw"

alias grr="python ~/Desktop/Data_Science/SPOTIPY/gdw/get_discover_weekly.py --rr"

Then grr or gdw on the command line will get the Release Radar or Discover Weekly playlist data.