Load VIAF API data to DuckDB
Build a VIAF API to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the VIAF API API base URL, auth, endpoints, and incremental loading.
VIAF is a library service that aggregates authority records from national libraries worldwide, providing a unified view of names and identities across different bibliographic systems. Everything needed to build a working VIAF 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 VIAF API to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from VIAF 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 VIAF 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.
VIAF API API at a glance
| Base URL | https://viaf.org |
| Example endpoint | GET viaf/search |
| Records found at | searchRetrieveResponse.records |
| Authentication | all requests are public and do not require authentication or a token |
| Pagination | Not paginated |
| Incremental field | startRecord |
| API reference | https://developer.api.oclc.org/viaf-api |
These values come from the VIAF API API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the VIAF API API?
The VIAF API is an open data service that does not require authentication or API keys for public endpoints. Requests are made directly over HTTP, often using the 'Accept' or 'httpAccept' headers to negotiate content formats like JSON.
No credentials required. The VIAF API API is public, so there is nothing to obtain and nothing to add to .dlt/secrets.toml — the pipeline above runs as written.
What VIAF API data can I load into DuckDB?
These are the VIAF API endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| viaf_cluster | /viaf/{id} | GET | Retrieves an Authority Cluster by its VIAF ID | |
| viaf_search | /viaf/search | GET | searchRetrieveResponse.records | Searches VIAF Authority clusters |
| viaf_autosuggest | /viaf/AutoSuggest | GET | Suggests possible matching authority clusters based on a string | |
| viaf_lccn | /viaf/lccn/{lccn} | GET | Translates LCCN ID to VIAF URI | |
| viaf_sourceid | /viaf/sourceID/{authoritySourceCode} | {localAuthorityId} | GET | |
| processed_record | /processed/{authoritySourceCode} | {localAuthorityId} | GET | |
| processed_search | /processed/search/processed | GET | Searches processed Authority Source records |
How do I load only new VIAF API records?
VIAF API exposes startRecord on viaf/search, 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": "viaf_search", "endpoint": { "path": "viaf/search", "data_selector": "searchRetrieveResponse.records", "incremental": {"cursor_path": "startRecord", "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 VIAF API pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /viaf/{id} and /viaf/search from the VIAF API API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def viaf_api_source(): config: RESTAPIConfig = { "client": { "base_url": "https://viaf.org", }, "resources": [ {"name": "viaf_search", "endpoint": {"path": "viaf/search", "data_selector": "searchRetrieveResponse.records"}}, {"name": "viaf_autosuggest", "endpoint": {"path": "viaf/AutoSuggest"}} ], } yield from rest_api_resources(config) def load_viaf_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="viaf_api_pipeline", destination="duckdb", dataset_name="viaf_api_data", ) load_info = pipeline.run(viaf_api_source()) print(load_info) if __name__ == "__main__": load_viaf_api_to_duckdb()
Run it with python viaf_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 VIAF 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("viaf_api_pipeline").dataset() df = data.viaf_search.df() print(df.head())
SQL:
SELECT * FROM viaf_api_data.viaf_search LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the VIAF 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 VIAF API 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 VIAF API 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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