Jonathon Broughton
140 lines
5.2 KiB
Python
140 lines
5.2 KiB
Python
from pydantic import Field
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from speckle_automate import AutomationContext, AutomateBase
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from Utilities.helpers import flatten_base, speckle_print
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import random
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class FunctionInputs(AutomateBase):
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"""These are function author defined values.
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Automate will make sure to supply them matching the types specified here.
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Please use the pydantic model schema to define your inputs:
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https://docs.pydantic.dev/latest/usage/models/
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"""
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comment_phrase: str = Field(
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title="Comment Phrase",
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description="This phrase will be added to a random model element.",
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)
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# We now want to specify the number of elements to which the comment phrase will be added.
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number_of_elements: int = Field(
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title="Number of Elements",
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description="The number of elements to which the comment phrase will be added.",
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)
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def automate_function(
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automate_context: AutomationContext,
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function_inputs: FunctionInputs,
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) -> None:
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"""This is an example Speckle Automate function.
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Args:
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automate_context: A context helper object, that carries relevant information
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about the runtime context of this function.
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It gives access to the Speckle project data, that triggered this run.
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It also has convenience methods attach result data to the Speckle model.
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function_inputs: An instance object matching the defined schema.
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"""
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# the context provides a convenient way, to receive the triggering version
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version_root_object = automate_context.receive_version()
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flat_list_of_objects = list(flatten_base(version_root_object))
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# filter the list to only include objects that are displayable.
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# this is a simple example, that checks if the object has a displayValue
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displayable_objects = [
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speckle_object
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for speckle_object in flat_list_of_objects
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if (
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getattr(speckle_object, "displayValue", None)
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or getattr(speckle_object, "@displayValue", None)
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)
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and getattr(speckle_object, "id", None) is not None
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]
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# a better displayable_objects should also include those instance objects that have a definition property
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# that cross-references to a speckle id, that is in turn displayable, so we need to add those objects to the list
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displayable_objects += [
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instance_object
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for instance_object in flat_list_of_objects
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if (
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getattr(instance_object, "definition", None)
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and (
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(
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getattr(
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getattr(instance_object, "definition"), "displayValue", None
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)
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or getattr(
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getattr(instance_object, "definition"), "@displayValue", None
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)
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)
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and getattr(getattr(instance_object, "definition"), "id", None)
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is not None
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)
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)
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]
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if len(displayable_objects) == 0:
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automate_context.mark_run_failed(
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"Automation failed: No displayable objects found."
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)
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else:
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# select a random object from the list
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# random_object = random.choice(displayable_objects)
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# instead of a single object we will select a random subset of displayable objects from the provided dataset
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real_number_of_elements = min(
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# We cant take more elements than we have
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function_inputs.number_of_elements,
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len(displayable_objects),
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)
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selected_objects = random.sample(
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displayable_objects,
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real_number_of_elements,
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)
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# create a list of object ids for all selected objects
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selected_object_ids = [obj.id for obj in selected_objects]
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# ACTIONS
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# attach comment phrase to all selected objects
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# it is possible to attach the same comment phrase to multiple objects
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# the category "Selected Objects" is used to group the objects in the viewer
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# grouping results in this way is a clean way to organize the objects in the viewer
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comment_message = f"{function_inputs.comment_phrase}"
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automate_context.attach_info_to_objects(
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category="Selected Objects",
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object_ids=selected_object_ids,
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message=comment_message,
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)
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# attach index as gradient value for all selected objects. this will be used for visualisation purposes
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# the category "Index Visualisation" is used to group the objects in the viewer
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gradient_values = {
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object_id: {"gradientValue": index + 1}
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for index, object_id in enumerate(selected_object_ids)
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}
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automate_context.attach_info_to_objects(
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category="Index Visualisation",
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metadata={
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"gradient": True,
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"gradientValues": gradient_values,
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},
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message="Object Indexes",
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object_ids=selected_object_ids,
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)
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automate_context.mark_run_success(
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f"Added comment to {real_number_of_elements} random objects."
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)
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# set the automation context view, to the original model / version view
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automate_context.set_context_view()
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