From 1d92dfa9573d2c9a113fcd0bbd6fc2d18941213e Mon Sep 17 00:00:00 2001
From: Jonathon Broughton <jonathon@stardotbmp.com>
Date: Tue, 12 Nov 2024 14:26:27 +0000
Subject: [PATCH] exercise 0

---
 Exercises/__init__.py            |  0
 Exercises/exercise-0/__init__.py |  0
 Exercises/exercise-0/function.py | 99 +++++++++++++++++---------------
 Exercises/exercise-0/inputs.py   |  8 +--
 4 files changed, 57 insertions(+), 50 deletions(-)
 create mode 100644 Exercises/__init__.py
 create mode 100644 Exercises/exercise-0/__init__.py

diff --git a/Exercises/__init__.py b/Exercises/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Exercises/exercise-0/__init__.py b/Exercises/exercise-0/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Exercises/exercise-0/function.py b/Exercises/exercise-0/function.py
index e6df6cf..638ef44 100644
--- a/Exercises/exercise-0/function.py
+++ b/Exercises/exercise-0/function.py
@@ -1,50 +1,57 @@
+import random
+
+from speckle_automate import AutomationContext
+
+from inputs import FunctionInputs
+from Utilities.flatten import flatten_base
+
+
 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 convenience methods attach 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()
-
-  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
-  ]
-
-  if len(displayable_objects) == 0:
-    automate_context.mark_run_failed(
-      "Automation failed: No displayable objects found."
-    )
-
-  else:
-    # select a random object from the list
-    random_object = random.choice(displayable_objects)
-
-    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.")
-
-  # set the automation context view, to the original model / version view
-  automate_context.set_context_view()
+    """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 convenience methods attach 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()
+
+    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
+    ]
+
+    if len(displayable_objects) == 0:
+        automate_context.mark_run_failed(
+          "Automation failed: No displayable objects found."
+        )
+
+    else:
+        # select a random object from the list
+        random_object = random.choice(displayable_objects)
+
+        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.")
+
+    # set the automation context view, to the original model / version view
+    automate_context.set_context_view()
diff --git a/Exercises/exercise-0/inputs.py b/Exercises/exercise-0/inputs.py
index 4ed70bf..c9788bd 100644
--- a/Exercises/exercise-0/inputs.py
+++ b/Exercises/exercise-0/inputs.py
@@ -10,7 +10,7 @@ class FunctionInputs(AutomateBase):
     https://docs.pydantic.dev/latest/usage/models/
     """
 
-  comment_phrase: str = Field(
-    title="Comment Phrase",
-    description="This phrase will be added to a random model element.",
-  )
+    comment_phrase: str = Field(
+      title="Comment Phrase",
+      description="This phrase will be added to a random model element.",
+    )