spotifyr

Overview

spotifyr is a 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

Development version (recommended)

devtools::install_github('charlie86/spotifyr')

The development version now includes functions from the geniusR package from Josiah Parry.

CRAN version 1.0.0 (Note: this is somewhat outdated, as it takes extra time to submit and pass CRAN checks)

install.packages('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()

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	64
A major	63
E major	58
G major	57
C major	49

Get your most recently played tracks

get_my_recently_played(limit = 5) %>% 
    select(track_name, artist_name, album_name, played_at_utc) %>% 
    kable()

track_name	artist_name	album_name	played_at_utc
DISKPREPT1	Aphex Twin	Computer Controlled Acoustic Instruments pt2 EP	2018-08-13 21:50:35
disk prep calrec2 barn dance [slo]	Aphex Twin	Computer Controlled Acoustic Instruments pt2 EP	2018-08-13 21:49:38
hat 2b 2012b	Aphex Twin	Computer Controlled Acoustic Instruments pt2 EP	2018-08-13 21:44:40
DISKPREPT4	Aphex Twin	Computer Controlled Acoustic Instruments pt2 EP	2018-08-13 21:43:14
piano un1 arpej	Aphex Twin	Computer Controlled Acoustic Instruments pt2 EP	2018-08-13 21:41:22

Find your all time favorite artists

get_my_top_artists(time_range = 'long_term', limit = 5) %>% 
    select(artist_name, artist_genres) %>% 
    rowwise %>% 
    mutate(artist_genres = paste(artist_genres, collapse = ', ')) %>% 
    ungroup %>% 
    kable()

artist_name	artist_genres
Radiohead	alternative rock, art rock, melancholia, modern rock, permanent wave, rock
Onra	alternative hip hop, chillhop, ninja, trip hop, wonky
Flying Lotus	alternative hip hop, chillwave, electronic, glitch, glitch hop, hip hop, indie r&b, indietronica, intelligent dance music, wonky
Teebs	abstract beats, bass music, chillwave, indietronica, wonky
Siriusmo	dance-punk, filter house, new rave

Find your favorite tracks at the moment

get_my_top_tracks(time_range = 'short_term', limit = 5) %>% 
    select(track_name, artist_name, album_name) %>% 
    kable()

track_name	artist_name	album_name
Bella	Wolfine	Bella
Drogba (Joanna)	Afro B	Drogba (Joanna)
Fellin' Myself	Mac Dre	Ronald Dregan For President 2004: Dreganomics
T69 collapse	Aphex Twin	T69 collapse
Not My Job	Mac Dre	The Genie Of The Lamp

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
These Days	0.949
Passover - 2007 Remastered Version	0.941
Colony - 2007 Remastered Version	0.808
Atrocity Exhibition - 2007 Remastered Version	0.787
Wilderness	0.775

Now if only there was some way to plot joy...

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

library(ggjoy)
#> Loading required package: ggridges
#> The ggjoy package has been deprecated. Please switch over to the
#> ggridges package, which provides the same functionality. Porting
#> guidelines can be found here:
#> https://github.com/clauswilke/ggjoy/blob/master/README.md

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")
#> Picking joint bandwidth of 0.112

Parallelization

get_artist_audio_features(), get_artist_albums(), get_album_tracks(), get_playlist_tracks(), and get_user_playlists() can run in parallel using the furrr package. To enable this feature, set parallelize = TRUE. You can also adjust the evaluation strategy by setting future_plan, which accepts a string matching one of the strategies implemented in future::plan() (defaults to "multiprocess").