Orb Python API Docs | dltHub

Orb is a REST API platform for product catalog, order, quote, and invoice management. The REST API base URL is https://api.base-orb.fr/v1/ and All requests require HTTP Basic Auth (username and API key) over HTTPS..

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 Orb data in under 10 minutes.

---

What data can I load from Orb?

Here are some of the endpoints you can load from Orb:

---

How do I authenticate with the Orb API?

Authentication uses HTTP Basic Auth: supply your username as the Basic Auth username and your API key as the password; all calls must be made over HTTPS.

1. Get your credentials

1. Log into your ORB account via the ORB dashboard.
2. Navigate to your profile page.
3. Locate the "API Key" field and copy the key.
4. Note your ORB username (shown on the profile header).
5. Use the username and API key for HTTP Basic Auth in API calls.

2. Add them to .dlt/secrets.toml

Copy
[sources.orb_subscriptions_source]
api_username = "your_orb_username"
api_key = "your_api_key_here"

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 Workbench:

Copy
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:

Copy
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 Orb 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 orb_subscriptions_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline orb_subscriptions_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 products and orders from the Orb 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 orb_subscriptions_source(api_username=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.base-orb.fr/v1/",
            "auth": {
                "type": "http_basic",
                "api_key": api_username,
            },
        },
        "resources": [
            {"name": "products", "endpoint": {"path": "products", "data_selector": "data"}},
            {"name": "orders", "endpoint": {"path": "orders", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="orb_subscriptions_pipeline",
        destination="duckdb",
        dataset_name="orb_subscriptions_data",
    )
    load_info = pipeline.run(orb_subscriptions_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("orb_subscriptions_pipeline").dataset()
sessions_df = data.products.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM orb_subscriptions_data.products LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("orb_subscriptions_pipeline").dataset()
data.products.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 Orb 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.

---

Troubleshooting

Authentication failures

If you receive a 401 Unauthorized response, ensure you are sending HTTP Basic Auth over HTTPS with the correct ORB username and API key. Verify that the API key is active and has permission for the requested endpoint.

Pagination and synchronization

The /products and /products/updates endpoints are paginated. Use the limit parameter to control page size and starting_after (or since for updates) to fetch subsequent pages. The updates response includes metadata.last_update_id; store this value and pass it as the since parameter on the next synchronization request.

Common HTTP errors

ORB follows standard HTTP status codes: 400 for malformed requests, 401 for authentication failures, 404 when a resource does not exist, and 5xx for server‑side problems. Rate‑limiting may result in 429 Too Many Requests; reduce request frequency or contact ORB support for quota adjustments.

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

---

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.

Copy
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