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Load Karaoke API data to DuckDB

Build a Karaoke API to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Karaoke API API base URL, auth, endpoints, and incremental loading.

SourceKaraoke APIKaraoke API API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

The Stingray Karaoke API is a service providing programmatic access to the Stingray Karaoke song catalog and player functionality. Everything needed to build a working Karaoke API → 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 Karaoke API to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

Prompt
Run uvx dlthub-init@latest to build a pipeline from Karaoke API 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 Karaoke API 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.


Karaoke API API at a glance

Base URLhttps://karaoke-api-service-prod.stingray.com/v1/
Example endpointGET artists
Authenticationrequests require a bearer token in the Authorization header and an API key in the X-API-KEY header — sent in the Authorization header, prefixed Bearer
PaginationNot paginated
Incremental fieldstart
API referencehttps://karaoke-api-doc.stingray.com/docs/introduction/getting-started/

These values come from the Karaoke API API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Karaoke API API?

The service requires both an API Key (sent via X-API-KEY header) and an OAuth2 Bearer token (sent via Authorization header).

1. Get your credentials

To obtain API credentials, navigate to your account dashboard on the provider's website (e.g., Karadeo or Voxmin). Locate the API management section or 'API Keys' dashboard. From there, select the option to generate a new API key. Ensure you copy the key immediately, as it may be hidden after the initial display. Follow any additional security prompts, such as naming the key for identification, and store the resulting secret securely, as it is required for authentication in the 'Authorization' header of your API requests.

2. Add them to .dlt/secrets.toml

[sources.karaoke_api_source] api_key = "your_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 Karaoke API data can I load into DuckDB?

These are the Karaoke API endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
artistsartistsGETRetrieves artist resources
songssongsGETRetrieves song resources
play_logv1/play-logPOSTCreates a play log for a song
pingv1/pingGETAPI connectivity check
karaokev3/karaokeGETRetrieves list of karaoke songs

How do I load only new Karaoke API records?

Karaoke API exposes start on artists, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

{"name": "artists", "endpoint": { "path": "artists", "incremental": {"cursor_path": "start", "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 Karaoke API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading transcribe and jobs from the Karaoke API API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def karaoke_api_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://karaoke-api-service-prod.stingray.com/v1/", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "artists", "endpoint": {"path": "artists"}}, {"name": "songs", "endpoint": {"path": "songs"}} ], } yield from rest_api_resources(config) def load_karaoke_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="karaoke_api_pipeline", destination="duckdb", dataset_name="karaoke_api_data", ) load_info = pipeline.run(karaoke_api_source()) print(load_info) if __name__ == "__main__": load_karaoke_api_to_duckdb()

Run it with python karaoke_api_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 Karaoke API 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("karaoke_api_pipeline").dataset() df = data.artists.df() print(df.head())

SQL:

SELECT * FROM karaoke_api_data.artists LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.


How do I deploy the Karaoke API 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 Karaoke API loads into governed, documented models.
  • Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →


What other destinations can I load Karaoke API data to?

dlt loads into any of these — only the destination argument changes:

DestinationExample 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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