Basic Function Change

main.py

@@ -1,6 +1,6 @@
 """This module contains the business logic of the function.
 
-Use the automation_context module to wrap your function in an Autamate context helper
+Use the automation_context module to wrap your function in an Automate context helper
 """
 
 from pydantic import Field
@@ -10,8 +10,6 @@ from speckle_automate import (
     execute_automate_function,
 )
 
-from flatten import flatten_base
-
 
 class FunctionInputs(AutomateBase):
     """These are function author defined values.
@@ -21,15 +19,6 @@ class FunctionInputs(AutomateBase):
     https://docs.pydantic.dev/latest/usage/models/
     """
 
-    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,
@@ -40,45 +29,10 @@ 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
-    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"
-            " ({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")
-
+    automate_context.mark_run_success("Successfully Sent to RealtimeLCA™ by Gaiup.")
 
 def automate_function_without_inputs(automate_context: AutomationContext) -> None:
     """A function example without inputs.
@@ -87,7 +41,7 @@ def automate_function_without_inputs(automate_context: AutomationContext) -> Non
      besides what the automation context provides,
      the inputs argument can be omitted.
     """
-    pass
+    automate_context.mark_run_success("Successfully Sent to Gaiup RealtimeLCA™.")
 
 
 # make sure to call the function with the executor
@@ -95,7 +49,4 @@ 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)
+    execute_automate_function(automate_function_without_inputs)