Load Coupa data to DuckDB
Build a Coupa to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Coupa API base URL, auth, endpoints, and incremental loading.
Coupa is a Business Spend Management (BSM) platform providing a REST API to manage core resources like purchase orders, invoices, and suppliers. Everything needed to build a working Coupa → 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 Coupa to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Coupa 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 Coupa 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.
Coupa API at a glance
| Base URL | https://{instance}.coupahost.com/api |
| Example endpoint | GET api/suppliers |
| Authentication | all requests require a Bearer token obtained via OAuth 2.0 flow — sent in the Authorization header, prefixed Bearer |
| Pagination | Offset-based page size via limit. Coupa uses offset-based pagination. Developers retrieve larger datasets by incrementing an 'offset' query parameter by the 'limit' value in a loop. Results are limited to 50 records per request. Some specific integration APIs may support 'page' based pagination, but core APIs rely on offset and limit. |
| Incremental field | updated_at |
| Record id | id |
| API reference | https://docs.coupa.com/en/developer-documentation/the-coupa-core-api/oauth-2.0-and-oidc |
These values come from the Coupa API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Coupa API?
Authentication is handled via OAuth 2.0 (OpenID Connect). An access token must be retrieved from the token endpoint and passed as a 'Bearer' token in the 'Authorization' header for all API requests.
1. Get your credentials
Coupa has deprecated traditional API keys in favor of OAuth 2.0/OIDC. To obtain credentials, follow these steps: 1. Log in to Coupa as an integrations-enabled administrator. 2. Navigate to Setup > Oauth2/OpenID Connect Clients. 3. Click Create. 4. Select Client Credentials as the Grant type. 5. Provide a name, login, and contact info, then save the client. 6. Once saved, note the Client Identifier (client_id) and Client Secret (client_secret). 7. Use these credentials to POST to https://<your_instance_domain>/oauth2/token to obtain an access_token, which must be refreshed periodically (Coupa recommends every 20 hours).
2. Add them to .dlt/secrets.toml
[sources.coupa_source] access_token = "REPLACE_ME"
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 Coupa data can I load into DuckDB?
These are the Coupa endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| suppliers | /api/suppliers | GET | Query list of suppliers | |
| purchase_orders | /api/purchase_orders | GET | Query list of purchase orders | |
| invoices | /api/invoices | GET | Query list of invoices | |
| users | /api/users | GET | Query list of users | |
| expense_reports | /api/expense_reports | GET | Query list of expense reports |
How do I load only new Coupa records?
Coupa exposes updated_at on api/suppliers, 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": "suppliers", "endpoint": { "path": "api/suppliers", "incremental": {"cursor_path": "updated_at", "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 Coupa pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /api/purchase_orders and /api/suppliers from the Coupa API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def coupa_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://{instance}.coupahost.com/api", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "suppliers", "endpoint": {"path": "api/suppliers"}}, {"name": "purchase_orders", "endpoint": {"path": "api/purchase_orders"}} ], } yield from rest_api_resources(config) def load_coupa_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="coupa_pipeline", destination="duckdb", dataset_name="coupa_data", ) load_info = pipeline.run(coupa_source()) print(load_info) if __name__ == "__main__": load_coupa_to_duckdb()
Run it with python coupa_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 Coupa 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("coupa_pipeline").dataset() df = data.suppliers.df() print(df.head())
SQL:
SELECT * FROM coupa_data.suppliers LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Coupa 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 Coupa 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 Coupa 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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