This repo provides tools for exploring the set lists on setlist.fm and related data. The functionality combines structured API calls to the setlist.fm API, with complementary web scraping for data not available there, such as venue capacity.
This repository aims to support ***non-***commercial computational methods for data science research, teaching, and general interest, promoting engagement with and understanding of the composition of setlists.
For more on the motivation, terminology and more please refer to our paper 'Mark Gotham and Shujin Gan, "Set Ready, Go! On the Structure of Live Music Setlists", forthcoming, 2025.' This is forthcoming; a pre-print is available on request. To cite this work, please refer to the paper and this repo (you are here).
For a tutorial-demonstration on APIs and concert setlists, head to the index.md file.
The main python files are named in the form
{where}_{what}_{how}.
E.g.,
setlistfm_events_api goes to
setlist.fm, and retrieves events using the api.
data: A place to store.csvfiles for whole events, albums, and related data in this project.- See note at
datasets/README.md
- See note at
distinct_setlist_IDs: A place to store.csvfiles for distinct setlist ids by artist.- See note at
distinct_setlist_IDs/README.md
- See note at
setlists: A place to store.jsonfiles, one per setlist named by the event ID..- See note at
setlists/README.md
- See note at
This repository is emphatically ***non-***commercial. It is intended for research, teaching, and general interest in the data science of setlists. We have read the terms of all relevant services, such as [setlist.fm's API service]https://www.setlist.fm/help/terms and believe that this repo is consistent with both the letter and spirit of those rules. Please make sure any downstream uses are similarly compliant. If you have any concerns, please reach out.
New code here is provided under the MIT licence.
New contributions to this repo, for bug fixes and additional functionality are welcome as long as they are consistent with the above.