examples

Lightning SDK Examples

Runnable Python and CLI examples for Lightning AI automation.

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Quick start • SDK tutorials • CLI tutorials • Running examples

Why these examples?

Each SDK tutorial has two parts:

• an executable .py file that can be run against a Lightning AI account
• a paired .rst guide that explains the workflow and keeps code snippets close to the runnable source

CLI tutorials use separate *_cli.rst files so shell workflows stay distinct from Python automation.

Build on Lightning AI, the platform for training, deploying, and scaling AI applications with managed compute, collaborative studios, and production endpoints.

Quick start

Install the SDK and authenticate:

pip install lightning-sdk
lightning login

Most examples need a Lightning AI teamspace. In docs and code snippets, owner/teamspace means the owner and teamspace name visible in Lightning AI. Replace placeholder names such as sdk-tutorial-studio with resources you can create or access.

Sandbox examples can also use a sandbox-scoped API key:

export LIGHTNING_SANDBOX_API_KEY="..."

SDK tutorials

Tutorial	Runnable file	What it shows
studios.rst	studios.py	Create, start, use, stop, and delete persistent studio workspaces
jobs.rst	jobs.py	Submit container-backed and studio-backed jobs, wait for completion, inspect status
mmts.rst	mmts.py	Run and inspect multi-machine training jobs
teamspaces.rst	teamspaces.py	Resolve account context and inspect teamspace resources
sandboxes.rst	sandboxes.py	Create disposable or persistent sandboxes, run commands, write files, resume, and delete

CLI tutorials

Tutorial	What it shows
studios_cli.rst	Create, start, connect to, copy files into, and stop studios from the CLI
jobs_cli.rst	Submit, inspect, list, stop, and delete jobs from the CLI
mmts_cli.rst	Launch and inspect multi-machine training runs from the CLI
teamspaces_cli.rst	Set CLI context and pass explicit teamspace scope to resource commands
sandboxes_cli.rst	Create sandboxes, run commands, inspect logs, stop, resume, and delete from the CLI
api_cli.rst	Call authenticated Lightning API endpoints directly from shell scripts

Running examples

Run SDK examples from this directory after authentication:

python sandboxes.py --teamspace owner/teamspace create
python jobs.py --teamspace my-teamspace --org my-org image

Run CLI examples from any directory:

lightning studio list --teamspace owner/teamspace
lightning deployment list --teamspace owner/teamspace

Use environment variables or CLI flags for secrets. Do not commit API keys, tokens, private keys, or downloaded credentials into example files.