Initial commit

main.py

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+"""This module contains the function's business logic.
+
+Use the automation_context module to wrap your function in an Automate context helper.
+"""
+
+from pydantic import Field, SecretStr
+from speckle_automate import (
+    AutomateBase,
+    AutomationContext,
+    execute_automate_function,
+)
+
+from flatten import flatten_base
+
+
+class FunctionInputs(AutomateBase):
+    """These are function author-defined values.
+
+    Automate will make sure to supply them matching the types specified here.
+    Please use the pydantic model schema to define your inputs:
+    https://docs.pydantic.dev/latest/usage/models/
+    """
+
+    # An example of 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."
+        ),
+    )
+
+
+def automate_function(
+    automate_context: AutomationContext,
+    function_inputs: FunctionInputs,
+) -> None:
+    """This is an example Speckle Automate function.
+
+    Args:
+        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 convenient methods for attaching result data to the Speckle model.
+        function_inputs: An instance object matching the defined schema.
+    """
+    # 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
+    ]
+    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"
+            f" ({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}",
+        )
+        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}"
+        )
+
+        # 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.")
+
+    # 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")
+
+
+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
+
+
+# make sure to call the function with the executor
+if __name__ == "__main__":
+    # NOTE: always pass in the automate function by its reference; do not invoke it!
+
+    # 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)