Load HCL Commerce data to DuckDB

HCL Commerce provides a set of REST APIs for managing e-commerce store resources, sessions, and user identities. Everything needed to build a working HCL Commerce → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

---

Build your HCL Commerce to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from HCL Commerce to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the HCL Commerce API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

---

HCL Commerce API at a glance

These values come from the HCL Commerce API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the HCL Commerce API?

Authentication is performed by obtaining tokens (WCToken and WCTrustedToken) via identity services (loginidentity, guestidentity, or ltpaidentity) and passing them in request headers, or by using HTTP Basic authentication with an 'Authorization' header containing a Base64-encoded 'username:password' string. HTTPS requests generally require both WCToken and WCTrustedToken headers, while HTTP requests may use only WCToken.

1. Get your credentials

HCL Commerce does not utilize a single 'API Key' setup via a central dashboard for REST API access. Instead, authentication is performed via identity services. To obtain credentials for programmatic access: 1) Identify your target environment's authentication endpoint (typically /loginidentity or /guestidentity). 2) For registered users, send a POST request with the user's login ID and password to the /loginidentity service to retrieve a WCToken (or LTPA token). 3) For guest access, use the /guestidentity service to create a session identity. 4) Use the returned token in the 'WCToken' header (or 'Authorization' header for basic authentication) for all subsequent API requests.

2. Add them to .dlt/secrets.toml

Copy
[sources.hcl_commerce_source]
base_url = "https://your-commerce-host.com/wcs/resources"
api_token = "your_retrieved_wctoken_here"
# If using basic auth instead:
# username = "your_username"
# password = "your_password"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

---

What HCL Commerce data can I load into DuckDB?

These are the HCL Commerce endpoints dlt can load into DuckDB:

---

How do I load only new HCL Commerce records?

HCL Commerce exposes offset on store/{storeId}/productview, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

Copy
{"name": "storefront_products", "endpoint": {
    "path": "store/{storeId}/productview",
    "data_selector": "contents",
    "incremental": {"cursor_path": "offset", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

---

What does the generated HCL Commerce pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading loginidentity and guestidentity from the HCL Commerce API into DuckDB:

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

@dlt.source
def hcl_commerce_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<hostname>:<port>/wcs/resources",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": api_key},
        },
        "resources": [
            {"name": "storefront_products", "endpoint": {"path": "store/{storeId}/productview", "data_selector": "contents"}},
            {"name": "search_query_service", "endpoint": {"path": "search/resources/api/v2/products", "data_selector": "contents"}}
        ],
    }
    yield from rest_api_resources(config)


def load_hcl_commerce_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="hcl_commerce_pipeline",
        destination="duckdb",
        dataset_name="hcl_commerce_data",
    )
    load_info = pipeline.run(hcl_commerce_source())
    print(load_info)


if __name__ == "__main__":
    load_hcl_commerce_to_duckdb()

Run it with python hcl_commerce_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

---

How do I query HCL Commerce data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

Copy
import dlt

data = dlt.pipeline("hcl_commerce_pipeline").dataset()
df = data.products.df()
print(df.head())

SQL:

Copy
SELECT * FROM hcl_commerce_data.products LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

---

How do I deploy the HCL Commerce to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw HCL Commerce loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

---

What other destinations can I load HCL Commerce data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

---

Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack