SAP NetWeaver Business Warehouse Python API Docs | dltHub

SAP NetWeaver Business Warehouse (BW) OData API is an OData-based REST interface for querying SAP BW data, executing BEx queries, and accessing InfoProviders. The REST API base URL is https://<host>:<port>/sap/opu/odata/sap/ and all requests require a CSRF token fetched via an initial authenticated call and maintained via session cookies.

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 NetWeaver Business Warehouse data in under 10 minutes.

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What data can I load from SAP NetWeaver Business Warehouse?

Here are some of the endpoints you can load from SAP NetWeaver Business Warehouse:

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How do I authenticate with the SAP NetWeaver Business Warehouse API?

Authentication typically requires an initial request with Basic Auth to fetch a CSRF token (passing 'X-CSRF-Token: Fetch'), which is then returned in the response headers and must be provided in the 'X-CSRF-Token' header for subsequent stateful operations.

1. Get your credentials

SAP NetWeaver Business Warehouse (BW) does not provide a traditional API key dashboard for REST access. Instead, follow these steps to manage and obtain credentials: 1. In your SAP system, use transaction SICF to locate or activate the necessary HTTP/REST service (e.g., OData services or InA services). 2. Create a dedicated technical user in transaction SU01 with the minimum required authorizations for the target services. 3. Ensure this user is assigned roles that provide access to the specific OData/InA service path. 4. Use these username and password credentials for Basic Authentication in your API calls. If the service is XSRF-protected, you must first perform an initial GET request to the service with the header 'X-CSRF-Token: Fetch' to retrieve a token, which must then be included in subsequent stateful requests.

2. Add them to .dlt/secrets.toml

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[sources.sap_netweaver_business_warehouse_source]
username = "your_sap_username"
password = "your_sap_password"
base_url = "https://your_sap_bw_host:port/sap/opu/odata/sap/"
client_id = "your_client_number"

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 NetWeaver Business Warehouse 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_netweaver_business_warehouse_pipeline.py

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

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Pipeline sap_netweaver_business_warehouse_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset sap_netweaver_business_warehouse_data
The duckdb destination used duckdb:/sap_netweaver_business_warehouse.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 /sap/bw/ina/ and /sap/opu/odata/sap/ from the SAP NetWeaver Business Warehouse 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_netweaver_business_warehouse_source(x_csrf_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<host>:<port>/sap/opu/odata/sap/",
            "auth": {"type": "bearer", "token": x_csrf_token},
        },
        "resources": [
            {"name": "bw_queries", "endpoint": {"path": "RSOD_BW_QUERY_SRV/Queries", "data_selector": "d"}},
            {"name": "info_providers", "endpoint": {"path": "RSOD_INFOPROV_SRV/InfoProviders", "data_selector": "d"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sap_netweaver_business_warehouse_pipeline",
        destination="duckdb",
        dataset_name="sap_netweaver_business_warehouse_data",
    )
    load_info = pipeline.run(sap_netweaver_business_warehouse_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_netweaver_business_warehouse_pipeline").dataset()
sessions_df = data.bw_queries.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM sap_netweaver_business_warehouse_data.bw_queries LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("sap_netweaver_business_warehouse_pipeline").dataset()
data.bw_queries.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 NetWeaver Business Warehouse 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