Atum REST API Python API Docs | dltHub

Atum is a WooCommerce/WordPress plugin exposing inventory and stock‑management endpoints (ATUM REST API) for programmatic access to ATUM resources via the WooCommerce REST API (wc/v3). The REST API base URL is https://{your_store_domain}/wp-json/wc/v3 and HTTP Basic Auth using WooCommerce REST API consumer key and secret (or consumer_key/consumer_secret query params)..

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 Atum REST API data in under 10 minutes.

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What data can I load from Atum REST API?

Here are some of the endpoints you can load from Atum REST API:

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How do I authenticate with the Atum REST API API?

Authenticate over HTTPS using HTTP Basic Auth: provide the REST API Consumer Key as username and Consumer Secret as password (curl: -u consumer_key:consumer_secret). If server strips Authorization header, pass consumer_key and consumer_secret as query string parameters.

1. Get your credentials

1. In your WordPress admin go to WooCommerce > Settings > Advanced > REST API.
2. Click 'Add key' (or the equivalent).
3. Enter a description, select the user, and choose permissions (read or read/write).
4. Save to generate Consumer Key and Consumer Secret.
5. Use Consumer Key as username and Consumer Secret as password for requests.

2. Add them to .dlt/secrets.toml

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[sources.atum_rest_api_source]
consumer_key = "ck_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
consumer_secret = "cs_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

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 Atum REST API 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 atum_rest_api_pipeline.py

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

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Pipeline atum_rest_api_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset atum_rest_api_data
The duckdb destination used duckdb:/atum_rest_api.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 atum_rest_api_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 purchase_orders and inventories from the Atum REST API 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 atum_rest_api_source(consumer_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your_store_domain}/wp-json/wc/v3",
            "auth": {
                "type": "http_basic",
                "consumer_key": consumer_key,
            },
        },
        "resources": [
            {"name": "purchase_orders", "endpoint": {"path": "atum/purchase-orders"}},
            {"name": "inventories", "endpoint": {"path": "atum/inventories"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="atum_rest_api_pipeline",
        destination="duckdb",
        dataset_name="atum_rest_api_data",
    )
    load_info = pipeline.run(atum_rest_api_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("atum_rest_api_pipeline").dataset()
sessions_df = data.purchase_orders.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM atum_rest_api_data.purchase_orders LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("atum_rest_api_pipeline").dataset()
data.purchase_orders.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 Atum REST API 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 failures

Ensure you use the Consumer Key as username and Consumer Secret as password over HTTPS. If you receive "Consumer key is missing" or 401/403 responses, try using query‑string authentication (append consumer_key and consumer_secret to the request) — some servers strip Authorization headers.

Pagination and large result sets

Many list endpoints support page and per_page query parameters. Default per_page is 10. Use page and per_page to iterate. Watch for server‑imposed maximum per_page limits; use incremental paging to avoid timeouts.

API error format and resource‑not‑found

ATUM/WooCommerce errors return an object with keys code (string), message (string) and data (object with status). Example:

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{ "code": "atum_rest_term_invalid", "message": "Resource doesn't exist.", "data": { "status": 404 } }

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