learning

AutomationML Learning Path

These notebooks are executable lessons built against the SDK's public API. Run them in order:

1. 01_build-a-drive-station.ipynb develops a motor and power-supply scenario from concrete instances to links and stable class semantics.
2. 02_json-and-xml-exchange.ipynb gives JSON and XML serialization its own focused lesson and proves that both formats reconstruct the same model.
3. 03_inheritance-interfaces-and-validation.ipynb investigates class inheritance and interface warnings, repairs a robot-cell instance, and adds a valid InternalLink.

Start locally

From the repository root:

python -m pip install -e ".[learning]"
jupyter lab learning

Open the first notebook and use Run All Cells. Each lesson includes prediction prompts, executable checks, and optional exercises. The committed notebooks start without stored outputs so every learner produces the results locally.