Exercise 1
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from pydantic import Field
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from speckle_automate import AutomationContext, AutomateBase
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from Utilities.helpers import flatten_base
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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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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 = 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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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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automate_context.attach_info_to_objects(
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category="Selected Object",
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object_ids=[random_object.id],
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message=function_inputs.comment_phrase,
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)
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automate_context.mark_run_success("Added a comment to a random object.")
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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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