Load setlist.fm data to DuckDB
Build a setlist.fm to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the setlist.fm API base URL, auth, endpoints, and incremental loading.
setlist.fm is a crowd-sourced concert setlist database that provides read-only REST API access to artists, setlists, venues, cities, and countries. Everything needed to build a working setlist.fm → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.
Build your setlist.fm to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from setlist.fm to DuckDB and run it on dltHub
That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the setlist.fm API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →
Prefer to write it yourself? Every fact the agent uses is below.
setlist.fm API at a glance
| Base URL | https://api.setlist.fm/rest/1.0 |
| Example endpoint | GET 1.0/artist/{mbid}/setlists |
| Records found at | setlist |
| Authentication | all requests require an API key passed in the x-api-key request header — sent in the x-api-key header |
| Pagination | Page-number |
| API reference | https://api.setlist.fm/docs/1.0/index.html |
These values come from the setlist.fm API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the setlist.fm API?
Authentication is performed by passing a valid API key in the 'x-api-key' HTTP request header. To receive JSON responses (instead of the default XML), you must also include the 'Accept: application/json' header.
1. Get your credentials
- Register for a free account at https://www.setlist.fm/signup or log in if you already have one at https://www.setlist.fm/login.
- Navigate to the API application page at https://www.setlist.fm/settings/api.
- Complete the API application form to request an API key.
- Once approved, you will be able to access your API key within your account settings.
- Use this key as an x-api-key header in your HTTP requests.
2. Add them to .dlt/secrets.toml
[sources.setlist_fm_source] api_key = "your_setlist_fm_api_key_here"
dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.
What setlist.fm data can I load into DuckDB?
These are the setlist.fm endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| search_setlists | search/setlists | GET | setlist | Search for setlists by artist, city, venue, or date. |
| artist_setlists | artist/{mbid}/setlists | GET | setlist | Get a list of an artist's setlists. |
| search_artists | search/artists | GET | artist | Search for artists. |
| search_cities | search/cities | GET | city | Search for cities. |
| search_venues | search/venues | GET | venue | Search for venues. |
How do I load only new setlist.fm records?
The setlist.fm API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.
{"name": "artist_setlists", "endpoint": { "path": "1.0/artist/{mbid}/setlists", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"}, }}
On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.
What does the generated setlist.fm pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /1.0/search/setlists and /1.0/artist/{mbid}/setlists from the setlist.fm API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def setlist_fm_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.setlist.fm/rest/1.0", "auth": {"type": "api_key", "api_key": api_key, "name": "x-api-key", "location": "header"}, }, "resources": [ {"name": "artist_setlists", "endpoint": {"path": "1.0/artist/{mbid}/setlists", "data_selector": "setlist"}}, {"name": "search_setlists", "endpoint": {"path": "1.0/search/setlists", "data_selector": "setlist"}} ], } yield from rest_api_resources(config) def load_setlist_fm_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="setlist_fm_pipeline", destination="duckdb", dataset_name="setlist_fm_data", ) load_info = pipeline.run(setlist_fm_source()) print(load_info) if __name__ == "__main__": load_setlist_fm_to_duckdb()
Run it with python setlist_fm_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query setlist.fm data in DuckDB?
dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.
Python (pandas DataFrame):
import dlt data = dlt.pipeline("setlist_fm_pipeline").dataset() df = data.artist_setlists.df() print(df.head())
SQL:
SELECT * FROM setlist_fm_data.artist_setlists LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the setlist.fm to DuckDB pipeline in production?
The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.
- Deploy & schedule — run the pipeline as a managed job with automatic retries.
- Monitor — observable job queues, alerting, and load metrics for every run.
- Transform — promote raw setlist.fm loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load setlist.fm data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.
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