R Wrapper for the 'Spotify' Web API • spotifyr

Overview

spotifyr is an R wrapper for pulling track audio features and other information from Spotify’s Web API in bulk. By automatically batching API requests, it allows you to enter an artist’s name and retrieve their entire discography in seconds, along with Spotify’s audio features and track/album popularity metrics. You can also pull song and playlist information for a given Spotify User (including yourself!).

Installation

CRAN version 2.1.0 (recommended)

install.packages('spotifyr')

Development version

devtools::install_github('charlie86/spotifyr')

Authentication

First, set up a Dev account with Spotify to access their Web API here. This will give you your Client ID and Client Secret. Once you have those, you can pull your access token into R with get_spotify_access_token().

The easiest way to authenticate is to set your credentials to the System Environment variables SPOTIFY_CLIENT_ID and SPOTIFY_CLIENT_SECRET. The default arguments to get_spotify_access_token() (and all other functions in this package) will refer to those. Alternatively, you can set them manually and make sure to explicitly refer to your access token in each subsequent function call.

Sys.setenv(SPOTIFY_CLIENT_ID = 'xxxxxxxxxxxxxxxxxxxxx')
Sys.setenv(SPOTIFY_CLIENT_SECRET = 'xxxxxxxxxxxxxxxxxxxxx')

access_token <- get_spotify_access_token()

Authorization code flow

For certain functions and applications, you’ll need to log in as a Spotify user. To do this, your Spotify Developer application needs to have a callback url. You can set this to whatever you want that will work with your application, but a good default option is http://localhost:1410/ (see image below). For more information on authorization, visit the offical Spotify Developer Guide.

Usage

What was The Beatles’ favorite key?

library(spotifyr)
beatles <- get_artist_audio_features('the beatles')

library(tidyverse)
library(knitr)

beatles %>% 
    count(key_mode, sort = TRUE) %>% 
    head(5) %>% 
    kable()

key_mode	n
D major	24
G major	21
A major	13
F major	12
C major	11

Get your most recently played tracks

library(lubridate)

get_my_recently_played(limit = 5) %>% 
    mutate(artist.name = map_chr(track.artists, function(x) x$name[1]),
           played_at = as_datetime(played_at)) %>% 
    select(track.name, artist.name, track.album.name, played_at) %>% 
    kable()

track.name	artist.name	track.album.name	played_at
Take The Power Back	Rage Against The Machine	Rage Against The Machine - XX (20th Anniversary Special Edition)	2020-02-15 18:18:30
Killing In The Name	Rage Against The Machine	Rage Against The Machine - XX (20th Anniversary Special Edition)	2020-02-15 18:08:24
Bombtrack	Rage Against The Machine	Rage Against The Machine - XX (20th Anniversary Special Edition)	2020-02-15 18:03:09
Testify	Rage Against The Machine	The Battle Of Los Angeles	2020-02-15 17:59:07
War Within a Breath	Rage Against The Machine	The Battle Of Los Angeles	2020-02-15 17:54:41

Find your all time favorite artists

get_my_top_artists_or_tracks(type = 'artists', time_range = 'long_term', limit = 5) %>% 
    select(name, genres) %>% 
    rowwise %>% 
    mutate(genres = paste(genres, collapse = ', ')) %>% 
    ungroup %>% 
    kable()

name	genres
Radiohead	alternative rock, art rock, melancholia, oxford indie, permanent wave, rock
Flying Lotus	afrofuturism, alternative hip hop, electronica, escape room, experimental hip hop, glitch, glitch hop, hip hop, indietronica, intelligent dance music, jazztronica, wonky
Onra	chillhop, japanese chillhop, wonky
Teebs	bass music, chillwave, electronica, experimental pop, indie jazz, indie r&b, indietronica, microhouse, wonky
Pixies	alternative rock, art rock, boston rock, garage rock, modern rock, noise pop, permanent wave, rock

Find your favorite tracks at the moment

get_my_top_artists_or_tracks(type = 'tracks', time_range = 'short_term', limit = 5) %>% 
    mutate(artist.name = map_chr(artists, function(x) x$name[1])) %>% 
    select(name, artist.name, album.name) %>% 
    kable()

name	artist.name	album.name
Testify	Rage Against The Machine	The Battle Of Los Angeles
Guerrilla Radio	Rage Against The Machine	The Battle Of Los Angeles
Killing In The Name	Rage Against The Machine	Rage Against The Machine - XX (20th Anniversary Special Edition)
One for Nujabes	.Sinh	One for Nujabes
Lantern Flies in Mist	Black Taffy	Elder Mantis

What’s the most joyful Joy Division song?

My favorite audio feature has to be “valence,” a measure of musical positivity.

joy <- get_artist_audio_features('joy division')

joy %>% 
    arrange(-valence) %>% 
    select(track_name, valence) %>% 
    head(5) %>% 
    kable()

track_name	valence
Passover - 2007 Remaster	0.941
Passover - 2007 Remaster	0.941
Colony - 2007 Remaster	0.808
Colony - 2007 Remaster	0.808
Atrocity Exhibition - 2007 Remaster	0.787

Now if only there was some way to plot joy…

Joyplot of the emotional rollercoasters that are Joy Division’s albums

library(ggjoy)

ggplot(joy, aes(x = valence, y = album_name)) + 
    geom_joy() + 
    theme_joy() +
    ggtitle("Joyplot of Joy Division's joy distributions", subtitle = "Based on valence pulled from Spotify's Web API with spotifyr")