SAP BW Open Hub Application Server Python API Docs | dltHub

SAP BW Open Hub is a service designed for distributing data from an SAP Business Warehouse system to non-SAP downstream systems and data marts. The REST API base URL is N/A (The Open Hub service does not expose a standard public REST API; connectivity is provided via SAP Gateway OData services or RFC). and The standard interface for SAP BW Open Hub uses SAP Basic authentication (username/password) via RFC..

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 pip install "dlt[workspace]" and start loading SAP BW Open Hub Application Server data in under 10 minutes.

---

What data can I load from SAP BW Open Hub Application Server?

Here are some of the endpoints you can load from SAP BW Open Hub Application Server:

---

How do I authenticate with the SAP BW Open Hub Application Server API?

The SAP BW Open Hub service utilizes ABAP-based function modules (e.g., RSB_API_OHS_DEST_GETLIST) rather than a REST API; external connectivity to the Open Hub service is typically established via RFC (Remote Function Call) or dedicated OData services provided through SAP Gateway Foundation.

1. Get your credentials

To obtain credentials for an SAP BW Open Hub integration, create a dedicated SAP user account using transaction code SU01. Assign this user the appropriate authorization role (e.g., /GOOG/BWOH_CDF_AUTH or a custom role containing the necessary RFC and SAP BW execution permissions). The recommended user type is a Communication user (Type C) for basic authentication or a System user (Type B) for OAuth 2.0. Ensure the user has permissions for authorization objects such as S_SDSAUTH.

2. Add them to .dlt/secrets.toml

Copy
[sources.sap_bw_open_hub_application_server_source]
sap_bw_username = "your_sap_username"
sap_bw_password = "your_sap_password"
sap_client = "800"
sap_host = "your_sap_app_server_host"
sap_system_number = "00"

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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI harness:

Copy
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:

Copy
dlthub ai toolkit rest-api-pipeline install

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 BW Open Hub Application Server 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:

Copy
python sap_bw_open_hub_application_server_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline sap_bw_open_hub_application_server_pipeline show

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

---

Python pipeline example

This example loads RSB_API_OHS_DEST_READ_DATA and RSB_API_OHS_DEST_GETLIST from the SAP BW Open Hub Application Server API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def sap_bw_open_hub_application_server_source(credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "N/A (The Open Hub service does not expose a standard public REST API; connectivity is provided via SAP Gateway OData services or RFC).",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": credentials},
        },
        "resources": [
            {"name": "open_hub_destinations", "endpoint": {"path": "sap/opu/odata/sap/ODP_BW_SRV/OpenHubDestinations", "data_selector": "d.results"}},
            {"name": "open_hub_data_delta", "endpoint": {"path": "sap/opu/odata/sap/ODP_BW_SRV/DeltaLinksOf{id}('{token}')/ChangesAfter", "data_selector": "d.results"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sap_bw_open_hub_application_server_pipeline",
        destination="duckdb",
        dataset_name="sap_bw_open_hub_application_server_data",
    )
    load_info = pipeline.run(sap_bw_open_hub_application_server_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.

---

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):

Copy
import dlt

data = dlt.pipeline("sap_bw_open_hub_application_server_pipeline").dataset()
sessions_df = data.open_hub_destinations.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM sap_bw_open_hub_application_server_data.open_hub_destinations LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("sap_bw_open_hub_application_server_pipeline").dataset()
data.open_hub_destinations.df().head()

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

---

What destinations can I load SAP BW Open Hub Application Server 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.

---

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.

Copy
dlthub ai toolkit data-exploration install
dlthub ai toolkit dlthub-platform install

• 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