Load WooCommerce data to DuckDB
Build a WooCommerce to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the WooCommerce API base URL, auth, endpoints, and incremental loading.
WooCommerce is an open-source e-commerce platform that exposes a REST API for programmatic access to store data including products, orders, and customers. Everything needed to build a working WooCommerce → 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 WooCommerce to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from WooCommerce 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 WooCommerce 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.
WooCommerce API at a glance
| Base URL | https://{your_store_domain}/wp-json/wc/v3 |
| Example endpoint | GET wc/v3/products |
| Authentication | all requests require HTTP Basic Authentication or consumer key/secret query parameters — sent in the Authorization header |
| Pagination | Page-number page size via per_page |
| Incremental field | page |
| Record id | id |
| API reference | https://developer.woocommerce.com/docs/apis/rest-api/authentication/ |
These values come from the WooCommerce API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the WooCommerce API?
The WooCommerce REST API uses HTTP Basic Authentication, where the consumer key acts as the username and the consumer secret as the password. For environments where the Authorization header is stripped or restricted, these credentials can be passed as query string parameters (consumer_key and consumer_secret).
1. Get your credentials
- Log in to your WordPress dashboard. 2. Navigate to WooCommerce > Settings > Advanced. 3. Click on the REST API tab. 4. Click the Add key button. 5. Enter a description, select a WordPress user, and set the permissions (Read, Write, or Read/Write). 6. Click Generate API key. 7. Copy the generated Consumer Key and Consumer Secret immediately, as the Secret will be hidden once you navigate away from the page.
2. Add them to .dlt/secrets.toml
[sources.woocommerce_source] url = "https://yourstore.com" consumer_key = "ck_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" consumer_secret = "cs_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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 WooCommerce data can I load into DuckDB?
These are the WooCommerce endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| products | /wc/v3/products | GET | List all products | |
| orders | /wc/v3/orders | GET | List all orders | |
| customers | /wc/v3/customers | GET | List all customers | |
| coupons | /wc/v3/coupons | GET | List all coupons | |
| product_categories | /wc/v3/products/categories | GET | List all product categories |
How do I load only new WooCommerce records?
WooCommerce exposes page on wc/v3/products, 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.
{"name": "products", "endpoint": { "path": "wc/v3/products", "incremental": {"cursor_path": "page", "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 WooCommerce pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /products and /orders from the WooCommerce API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def woocommerce_source(consumer_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://{your_store_domain}/wp-json/wc/v3", "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": consumer_key}, }, "resources": [ {"name": "products", "endpoint": {"path": "wc/v3/products"}}, {"name": "orders", "endpoint": {"path": "wc/v3/orders"}} ], } yield from rest_api_resources(config) def load_woocommerce_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="woocommerce_pipeline", destination="duckdb", dataset_name="woocommerce_data", ) load_info = pipeline.run(woocommerce_source()) print(load_info) if __name__ == "__main__": load_woocommerce_to_duckdb()
Run it with python woocommerce_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 WooCommerce 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):
import dlt data = dlt.pipeline("woocommerce_pipeline").dataset() df = data.products.df() print(df.head())
SQL:
SELECT * FROM woocommerce_data.products LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the WooCommerce 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 WooCommerce loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load WooCommerce data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
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.
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