README.md
In dmi3kno/musicbrainz: Bindings for the 'musicbrainz' Database API

musicbrainz

The goal of musicbrainz is to make it easy to call the MusicBrainz Database API from R. Currently API does NOT require authentication for reading the data, however, requests to the database are subject to a rate limit of 1 request/sec. The package utilizes ratelimitr to make sure you don’t need to worry about exceeding that limit.

You can install musicbrainz from github with:

# install.packages("devtools")
devtools::install_github("dmi3kno/musicbrainz")

There are three families of functions in musicbrainz package: search, lookup and browse.

Lets search information about Miles Davis

library(musicbrainz)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

miles_df <- search_artists("Miles Davis")
#> Returning artists 1 to 25 of 2443
miles_df
#> # A tibble: 25 x 28
#>    mbid  type  type_id score name  sort_name gender gender_id country
#>    <chr> <chr> <chr>   <int> <chr> <chr>     <chr>  <lgl>     <chr>  
#>  1 561d… Pers… b6e035…   100 Mile… Davis, M… male   NA        US     
#>  2 fe72… Group e431f5…    86 Mile… Davis, M… <NA>   NA        US     
#>  3 16d2… Group e431f5…    80 The … Davis, M… <NA>   NA        <NA>   
#>  4 f137… Group e431f5…    79 Mile… Davis, M… <NA>   NA        <NA>   
#>  5 0360… Group e431f5…    77 Mile… Davis, M… <NA>   NA        <NA>   
#>  6 8813… Group e431f5…    76 Mile… Davis, M… <NA>   NA        <NA>   
#>  7 d74d… Pers… b6e035…    76 Mile… Moody, M… <NA>   NA        <NA>   
#>  8 5464… Group e431f5…    76 Mile… Miles Da… <NA>   NA        <NA>   
#>  9 607d… Group e431f5…    69 Mile… Davis, M… <NA>   NA        <NA>   
#> 10 72f2… Group e431f5…    68 Mile… Davis, M… <NA>   NA        <NA>   
#> # … with 15 more rows, and 19 more variables: disambiguation <chr>,
#> #   area_id <chr>, area_name <chr>, area_sort_name <chr>,
#> #   area_disambiguation <lgl>, area_iso <lgl>, begin_area_id <chr>,
#> #   begin_area_name <chr>, begin_area_sort_name <chr>,
#> #   begin_area_disambiguation <lgl>, end_area_id <chr>, end_area_name <chr>,
#> #   end_area_sort_name <chr>, end_area_disambiguation <lgl>,
#> #   life_span_begin <chr>, life_span_end <chr>, life_span_ended <lgl>,
#> #   ipis <chr>, isnis <chr>

It looks like the first hit is what we need. We can use dplyr to extract the information of interest

miles_id <- miles_df %>% 
  select(mbid) %>%
  slice(1) %>% 
  pull()

Now that we have MusicBrainz id (“mbid”) we can call the lookup function.

miles_lookup <- lookup_artist_by_id("561d854a-6a28-4aa7-8c99-323e6ce46c2a")
miles_lookup
#> # A tibble: 1 x 28
#>   mbid  type  type_id score name  sort_name gender gender_id country
#>   <chr> <chr> <chr>   <chr> <chr> <chr>     <chr>  <chr>     <chr>  
#> 1 561d… Pers… b6e035… <NA>  Mile… Davis, M… Male   36d3d30a… US     
#> # … with 19 more variables: disambiguation <chr>, area_id <chr>,
#> #   area_name <chr>, area_sort_name <chr>, area_disambiguation <chr>,
#> #   area_iso <chr>, begin_area_id <chr>, begin_area_name <chr>,
#> #   begin_area_sort_name <chr>, begin_area_disambiguation <chr>,
#> #   end_area_id <chr>, end_area_name <chr>, end_area_sort_name <chr>,
#> #   end_area_disambiguation <chr>, life_span_begin <chr>, life_span_end <chr>,
#> #   life_span_ended <lgl>, ipis <chr>, isnis <chr>

We can also browse linked records (such as all releases by Miles Davis).

miles_releases <- browse_releases_by("artist", "561d854a-6a28-4aa7-8c99-323e6ce46c2a")
#> Returning releases 1 to 25 of 1267
miles_releases
#> # A tibble: 25 x 17
#>    mbid  score count title status status_id packaging_id packaging_name date 
#>    <chr> <int> <lgl> <chr> <chr>  <chr>     <lgl>        <lgl>          <chr>
#>  1 16ed…    NA NA    Mile… Offic… 4e304316… NA           NA             1954 
#>  2 20ff…    NA NA    I've… Offic… 4e304316… NA           NA             1953 
#>  3 3bdb…    NA NA    Yest… Offic… 4e304316… NA           NA             1951 
#>  4 49aa…    NA NA    Youn… <NA>   <NA>      NA           NA             1952 
#>  5 4a8c…    NA NA    Clas… Offic… 4e304316… NA           NA             1954 
#>  6 596f…    NA NA    Blue… Offic… 4e304316… NA           NA             1955 
#>  7 645a…    NA NA    The … Offic… 4e304316… NA           NA             1953 
#>  8 6c10…    NA NA    Budo… Offic… 4e304316… NA           NA             1949…
#>  9 7acd…    NA NA    Mile… Offic… 4e304316… NA           NA             1955…
#> 10 8292…    NA NA    Mile… Offic… 4e304316… NA           NA             1953 
#> # … with 15 more rows, and 8 more variables: country <chr>,
#> #   disambiguation <chr>, barcode <chr>, asin <lgl>, track_count <lgl>,
#> #   quality <chr>, release_group_id <lgl>, release_group_primary_type <lgl>