setlistkit

A generic, open-source setlist prediction toolkit. It ingests setlists from multiple sources, builds a catalog of songs, segues, families, and durations, and predicts what a band will play next. moe. is the first dataset it targets, not the limit of what it does.

Status: early development. The architecture is settled and the scaffold is in place; the ingest, catalog, model, and reporting layers are being built out phase by phase.

• State lives outside the repository. All mutable state sits under a data_root you point at from config. Nothing derived is committed.
• Band knowledge lives in data, not code. A band pack — a directory of JSON governed by a schema — carries the vocabulary, aliases, and classifier rules. Code is the last resort.
• The catalog stands alone. Someone who wants a jam-band song graph and no prediction can install setlistkit and use the catalog layer by itself. The layering is enforced by a test, not by convention.
• Be a good network citizen. Every source client identifies itself with a mandatory User-Agent, is cached and rate-limited, and backs off on error. setlistkit ships no scraper that violates a source's terms.

setlistkit develops against Python 3.14 and supports 3.11+ (it uses the standard-library tomllib). The reporting extra pulls in the presentational dependencies:

pip install setlistkit           # core: catalog, model, picks
pip install 'setlistkit[report]' # adds the themeable dashboards and feeds

Copy slkit.example.toml to slkit.toml and edit it. At minimum you must set data_root and change user_agent from its placeholder — until you do, any command that would touch the network refuses to run.

slkit config show    # print the resolved configuration
slkit config check   # validate it, including network identity

AGPL-3.0-or-later, © Tim Case. This project is made possible by the people who transcribe setlists and tape shows, and a network-reaching copyleft keeps it available to them: nobody gets to take a hosted fork private.

A setlist — the songs played, their order, segues, and encore — is a human-entered fact about a public performance, and setlistkit stores those. It deliberately does not depend on the derived aggregates (play-frequency averages, historical base rates) that a tracker computes on top of them; those are the tracker's IP.