SDU Robotics UR RTDE Python API Docs | dltHub

UR RTDE is a C++ interface for controlling and receiving data from Universal Robots using the Real-Time Data Exchange (RTDE) and the robot dashboard. The REST API base URL is `` and No HTTP auth; connect to robot IP and TCP ports (RTDE port 30004, dashboard port 29999)..

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 SDU Robotics UR RTDE data in under 10 minutes.

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What data can I load from SDU Robotics UR RTDE?

Here are some of the endpoints you can load from SDU Robotics UR RTDE:

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How do I authenticate with the SDU Robotics UR RTDE API?

The ur_rtde library communicates over TCP to the robot. There is no HTTP authentication; network access to the robot IP and the appropriate ports is required. Access control is handled by the robot and network configuration.

1. Get your credentials

1. Ensure you have network access to the robot's IP address.
2. Verify that ports 30004 (RTDE) and 29999 (Dashboard) are open in any firewalls.
3. Configure the robot controller to allow external connections if required.
4. No API keys or tokens need to be generated; the robot's network settings provide the necessary access.

2. Add them to .dlt/secrets.toml

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[sources.sdu_robotics_ur_rtde_source]
robot_host = "192.168.0.10"
rtde_port = 30004
dash_port = 29999

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

1. Install the dlt AI Workbench:

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dlt 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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dlt 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 SDU Robotics UR RTDE 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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python sdu_robotics_ur_rtde_pipeline.py

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

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Pipeline sdu_robotics_ur_rtde_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset sdu_robotics_ur_rtde_data
The duckdb destination used duckdb:/sdu_robotics_ur_rtde.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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dlt pipeline sdu_robotics_ur_rtde_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.

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Python pipeline example

This example loads rtde_receive and dashboard from the SDU Robotics UR RTDE 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 sdu_robotics_ur_rtde_source(robot_host=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "",
            "auth": {
                "type": "none",
                "": robot_host,
            },
        },
        "resources": [
            {"name": "rtde_receive", "endpoint": {"path": "connect to RTDE TCP at {robot_host}:30004"}},
            {"name": "dashboard", "endpoint": {"path": "connect to dashboard TCP at {robot_host}:29999"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sdu_robotics_ur_rtde_pipeline",
        destination="duckdb",
        dataset_name="sdu_robotics_ur_rtde_data",
    )
    load_info = pipeline.run(sdu_robotics_ur_rtde_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("sdu_robotics_ur_rtde_pipeline").dataset()
sessions_df = data.rtde_receive.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM sdu_robotics_ur_rtde_data.rtde_receive LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("sdu_robotics_ur_rtde_pipeline").dataset()
data.rtde_receive.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 SDU Robotics UR RTDE 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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Troubleshooting

Authentication / Connection failures

The API is not HTTP‑based. Connection failures are caused by network/firewall blocking or incorrect robot IP/port. Verify robot IP, ensure ports 30004 (RTDE) and 29999 (dashboard) are reachable, and that no firewall blocks TCP. Use isConnected() and reconnect() in the library.

Protocol negotiation / version mismatch

RTDE requires protocol negotiation. If negotiateProtocolVersion() fails, check robot firmware and ur_rtde library compatibility. Update robot controller firmware or use a matching library version.

Robot safety states and errors

Many operations fail if the robot is in protective stop, emergency stop, or not powered. Check getSafetyMode(), isProtectiveStopped(), isEmergencyStopped(), and getRobotStatus() before issuing motion commands. Dashboard commands (loadURP, play, stop) may throw exceptions if safety confirmations are required.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

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

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

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime 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