Policy and data regions

Argument	Type	Omitted	Workload file	HTTP field
`data_regions`	`list[str]`	No explicit region restriction from shortcut	`data_regions`	`policy.data_regions`
`policy`	Dictionary	Absent unless populated	Same key or table	`policy`

data_regions is a list of exact region identifiers accepted by your deployment. An empty list adds no location restriction. There is no universal region list or region-discovery method in this SDK. For the hosted service, contact Nodus for the enabled identifiers before setting a location restriction. For a private deployment, obtain them from its administrator. Do not assume a cloud provider's region codes are valid.

Restricting regions narrows eligible routes and can make a workload infeasible. The SDK forwards the identifiers without translating them.

Inside a with nodus.Client() as client: block:

Python

workload = client.run(
    image="pytorch/pytorch:2.8.0-cuda12.8-cudnn9-runtime",
    command=["python", "-c", "print('regional workload')"],
    data_regions=[],
    budget=5,
)

This example adds no region restriction. If your workload requires a particular geography, replace the empty list with the exact approved identifiers before submitting. Do not use unrestricted execution for a location-sensitive workload.

policy["data_regions"] wins over the flat data_regions argument. Regions belong under policy, not requirements. Omission does not promise execution in any particular geography. Deployment and account policies may still constrain it. policy.secret_refs accepts tenant secret names or IDs. Admission pins each version and supplies it as NODUS_SECRET_<NAME> in the execution environment. policy.egress_allow accepts HTTPS hostnames to add to a live connection's allowlist. These fields require an isolated execution provider.

Attach a wandb connection with connections=["lab-wandb"] and optionally set sweep_id="experiment-42" to group runs. See live connections for credential delivery, network restrictions and captured run links.