Reset main.py

main.py

@@ -1,16 +1,9 @@
-"""This module contains the business logic of the function.
+import random
 
-Use the automation_context module to wrap your function in an Autamate context helper
-"""
+from pydantic import Field
+from speckle_automate import AutomationContext, AutomateBase, execute_automate_function
 
-from pydantic import Field, SecretStr
-from speckle_automate import (
-    AutomateBase,
-    AutomationContext,
-    execute_automate_function,
-)
-
-from flatten import flatten_base
+from Utilities.helpers import flatten_base
 
 
 class FunctionInputs(AutomateBase):
@@ -21,14 +14,9 @@ class FunctionInputs(AutomateBase):
     https://docs.pydantic.dev/latest/usage/models/
     """
 
-    # an example how to use secret values
-    whisper_message: SecretStr = Field(title="This is a secret message")
-    forbidden_speckle_type: str = Field(
-        title="Forbidden speckle type",
-        description=(
-            "If a object has the following speckle_type,"
-            " it will be marked with an error."
-        ),
+    comment_phrase: str = Field(
+        title="Comment Phrase",
+        description="This phrase will be added to a random model element.",
     )
 
 
@@ -42,54 +30,46 @@ def automate_function(
         automate_context: A context helper object, that carries relevant information
             about the runtime context of this function.
             It gives access to the Speckle project data, that triggered this run.
-            It also has conveniece methods attach result data to the Speckle model.
+            It also has convenience methods attach result data to the Speckle model.
         function_inputs: An instance object matching the defined schema.
     """
-    # the context provides a conveniet way, to receive the triggering version
+
+    # the context provides a convenient way, to receive the triggering version
     version_root_object = automate_context.receive_version()
 
-    objects_with_forbidden_speckle_type = [
-        b
-        for b in flatten_base(version_root_object)
-        if b.speckle_type == function_inputs.forbidden_speckle_type
+    flat_list_of_objects = flatten_base(version_root_object)
+
+    # filter the list to only include objects that are displayable.
+    # this is a simple example, that checks if the object has a displayValue
+    displayable_objects = [
+        speckle_object
+        for speckle_object in flat_list_of_objects
+        if (
+            getattr(speckle_object, "displayValue", None)
+            or getattr(speckle_object, "@displayValue", None)
+        )
+        and getattr(speckle_object, "id", None) is not None
     ]
-    count = len(objects_with_forbidden_speckle_type)
 
-    if count > 0:
-        # this is how a run is marked with a failure cause
-        automate_context.attach_error_to_objects(
-            category="Forbidden speckle_type"
-            " ({function_inputs.forbidden_speckle_type})",
-            object_ids=[o.id for o in objects_with_forbidden_speckle_type if o.id],
-            message="This project should not contain the type: "
-            f"{function_inputs.forbidden_speckle_type}",
-        )
+    if len(displayable_objects) == 0:
         automate_context.mark_run_failed(
-            "Automation failed: "
-            f"Found {count} object that have one of the forbidden speckle types: "
-            f"{function_inputs.forbidden_speckle_type}"
+            "Automation failed: No displayable objects found."
         )
 
-        # set the automation context view, to the original model / version view
-        # to show the offending objects
-        automate_context.set_context_view()
-
     else:
-        automate_context.mark_run_success("No forbidden types found.")
+        # select a random object from the list
+        random_object = random.choice(displayable_objects)
 
-    # if the function generates file results, this is how it can be
-    # attached to the Speckle project / model
-    # automate_context.store_file_result("./report.pdf")
+        automate_context.attach_info_to_objects(
+            category="Selected Object",
+            object_ids=[random_object.id],
+            message=function_inputs.comment_phrase,
+        )
 
+        automate_context.mark_run_success("Added a comment to a random object.")
 
-def automate_function_without_inputs(automate_context: AutomationContext) -> None:
-    """A function example without inputs.
-
-    If your function does not need any input variables,
-     besides what the automation context provides,
-     the inputs argument can be omitted.
-    """
-    pass
+    # set the automation context view, to the original model / version view
+    automate_context.set_context_view()
 
 
 # make sure to call the function with the executor
@@ -98,6 +78,3 @@ if __name__ == "__main__":
 
     # pass in the function reference with the inputs schema to the executor
     execute_automate_function(automate_function, FunctionInputs)
-
-    # if the function has no arguments, the executor can handle it like so
-    # execute_automate_function(automate_function_without_inputs)