SAP Ariba Python API Docs | dltHub

SAP Ariba provides a suite of REST APIs for procurement and supply chain management integration within the Ariba Network ecosystem. The REST API base URL is https://openapi.ariba.com/api (Note: The exact base URL and OAuth server prefix are region and API-specific, and must be retrieved from the SAP Ariba Developer Portal discovery page for the specific API). and Requires both an API Key and an OAuth 2.0 Bearer token for all requests..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv add "dlt[hub]" and start loading SAP Ariba data in under 10 minutes.

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What data can I load from SAP Ariba?

Here are some of the endpoints you can load from SAP Ariba:

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How do I authenticate with the SAP Ariba API?

SAP Ariba uses a combination of an API Key (sent in the 'apiKey' header) and an OAuth 2.0 Client Credentials flow (where the access token is sent in the 'Authorization' header as 'Bearer '). The OAuth token request requires a 'Basic' authorization header containing the Base64-encoded client ID and secret.

1. Get your credentials

To obtain credentials for SAP Ariba APIs, follow these steps in the SAP Ariba Developer Portal (https://developer.ariba.com/): 1. Log in to the portal as an Organization Admin. 2. Navigate to 'Manage' in the left menu and select 'Applications'. 3. Search for or create your application. 4. Retrieve the 'Application Key' directly from the application details. 5. To get the OAuth credentials, click 'Actions' > 'Generate OAuth Secret' for your application; ensure you copy the Client ID and Client Secret from the resulting pop-up immediately, as they are not stored by the system. 6. Ensure your application has been granted API access by your administrator.

2. Add them to .dlt/secrets.toml

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[sources.sap_ariba_source]
application_key = "your_application_key_here"
client_id = "your_oauth_client_id_here"
client_secret = "your_oauth_client_secret_here"
realm = "your_ariba_realm_name_here"
oauth_token_url = "https://api.ariba.com/v2/oauth/token"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv init
uv add "dlt[hub]"

1. Install the dlt AI harness:

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uv run dlthub ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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uv run dlthub ai toolkit install rest-api-pipeline

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the SAP Ariba API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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uv run python sap_ariba_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline sap_ariba_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset sap_ariba_data
The duckdb destination used duckdb:/sap_ariba.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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uv run dlthub show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads oauth/token and api-services (or specific resource endpoints like operationalreporting-job) from the SAP Ariba API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def sap_ariba_source(api_key_client_id_client_secret=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://openapi.ariba.com/api (Note: The exact base URL and OAuth server prefix are region and API-specific, and must be retrieved from the SAP Ariba Developer Portal discovery page for the specific API).",
            "auth": {"type": "bearer", "token": api_key_client_id_client_secret},
        },
        "resources": [
            {"name": "vendor_workspaces", "endpoint": {"path": "supplierdatapagination/v4/prod/vendors/{vendorId}/workspaces"}},
            {"name": "vendor_certificates", "endpoint": {"path": "supplierdatapagination/v4/prod/vendors/{vendorId}/certificates"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sap_ariba_pipeline",
        destination="duckdb",
        dataset_name="sap_ariba_data",
    )
    load_info = pipeline.run(sap_ariba_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("sap_ariba_pipeline").dataset()
sessions_df = data.vendor_workspaces.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM sap_ariba_data.vendor_workspaces LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("sap_ariba_pipeline").dataset()
data.vendor_workspaces.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load SAP Ariba data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI harness:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-platform — Deploy, schedule, and monitor your pipeline in production.

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uv run dlthub ai toolkit install data-exploration
uv run dlthub ai toolkit install dlthub-platform

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack