Exercise 0: Basic Automation 🚀

This exercise introduces the fundamental concepts of Speckle Automate by implementing a simple random comment function. It's based on the root main.py template.

Key Components 🔑

Inputs (`inputs.py`)

comment_phrase: str = Field(
    title="Comment Phrase",
    description="This phrase will be added to a random model element."
)

Single input parameter: comment_phrase
Uses Pydantic for input validation
Demonstrates basic input schema definition

Function (`function.py`)

def automate_function(automate_context: AutomationContext, function_inputs: FunctionInputs) -> None:
    # Get the version's root object
    version_root_object = automate_context.receive_version()

    # Get displayable objects, add comment to random one
    # ...

Demonstrates use of the AutomateContext for:

Loading model data
Attaching comments
Setting view state
Handling success/failure states

Function Flow 📊

Receives the version's root object
Flattens the object tree
Filters for displayable objects
Randomly selects one object
Attaches a comment to the selected object
Reports success or failure

Key Learning Points 📝

Understanding basic Automate function structure
Working with Speckle objects and their properties
Using AutomateContext for model interaction
Basic error handling and status reporting

Testing 🧪

Use the provided test file:

pytest tests/local_test_exercise0.py::test_function_run

README.md