Refactor code structure and file organization

- Renamed directories and files to follow a more organized structure
- Updated import statements in affected files to reflect the new directory structure

.github/workflows/main.yml

@@ -27,14 +27,14 @@ jobs:
       - name: Extract functionInputSchema
         id: extract_schema
         run: |
-          python main.py generate_schema ${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}
+          python src/main.py generate_schema ${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}
       - name: Speckle Automate Function - Build and Publish
         uses: specklesystems/[email protected]
         with:
           speckle_automate_url: ${{ env.SPECKLE_AUTOMATE_URL || 'https://automate.speckle.dev' }} 
           speckle_token: ${{ secrets.SPECKLE_FUNCTION_TOKEN }}
           speckle_function_id: ${{ secrets.SPECKLE_FUNCTION_ID }}
           speckle_function_input_schema_file_path: ${{ env.FUNCTION_SCHEMA_FILE_NAME }}
-          speckle_function_command: 'python -u main.py run'
+          speckle_function_command: 'python -u src/main.py run'
           speckle_function_recommended_cpu_m: 4000
           speckle_function_recommended_memory_mi: 4000

pyproject.toml

@@ -4,6 +4,7 @@ version = "0.1.0"
 description = "Examine model health by identifying areas of high mesh density as possible perfomance issues."
 authors = ["Jonathon Broughton <[email protected]>"]
 readme = "README.md"
+packages = [{ include = "src" }]
 
 [tool.poetry.dependencies]
 python = "^3.11"
@@ -25,6 +26,7 @@ requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.ruff]
+line-length = 88
 select = [
   "E",  # pycodestyle
   "F",  # pyflakes
@@ -34,4 +36,4 @@ select = [
 ]
 
 [tool.ruff.pydocstyle]
-convention = "google"
+convention = "google"

Objects/objects.py → src/Objects/objects.py

@@ -1,4 +1,3 @@
-import json
 import statistics
 from dataclasses import dataclass, field
 from typing import Any, Dict, Iterable, List, Optional, TypeVar, Union
@@ -11,7 +10,7 @@
 from specklepy.objects.other import RenderMaterial
 from specklepy.objects.primitive import Interval
 
-from Utilities.utilities import Utilities
+from src.Utilities import Utilities
 
 T = TypeVar("T", bound=Base)
 

Utilities/plotting.py → src/Utilities/plotting.py

@@ -127,4 +127,3 @@ def plot_area_distribution(areas: List[float]) -> None:
         plt.ylabel("Count")
         plt.title("Area Distribution")
         plt.grid(True)
-        # plt.show()

Utilities/reporting.py → src/Utilities/reporting.py

@@ -1,10 +1,10 @@
 import io
-import os
 import tempfile
 from datetime import datetime
 from pathlib import Path
 from typing import IO, Any, Dict, List, Union
 
+import httpx
 import matplotlib.pyplot as plt
 from PIL import Image as PILImage
 from reportlab.lib.colors import green, red
@@ -21,8 +21,8 @@
     TableStyle,
 )
 
-from Objects.objects import HealthObject
-from Utilities.plotting import Plotting
+from src.Objects.objects import HealthObject
+from src.Utilities.plotting import Plotting
 
 
 class Report:
@@ -260,3 +260,32 @@ def write_pdf_to_temp(report: IO[bytes]) -> str:
         temp_file.write_bytes(report.read())
 
         return str(temp_file)
+
+
+from speckle_automate import AutomationContext
+
+
+def safe_store_file_result(automate_context: AutomationContext, file_name: str):
+    # Store the original URL
+    original_url = automate_context.automation_run_data.speckle_server_url
+
+    try:
+        # Modify the URL property of the automation_run_data
+        automate_context.automation_run_data.speckle_server_url = original_url.rstrip(
+            "/"
+        )
+
+        # Attempt to store the file
+        automate_context.store_file_result(file_name)
+    except httpx.HTTPStatusError as e:
+        if e.response.status_code == 404:
+            # Handle the 404 error
+            error_message = f"Unable to store file: {file_name}. Error: {str(e)}"
+            print(error_message)  # For logging purposes
+            automate_context.mark_run_exception(error_message)
+
+        else:
+            raise
+    finally:
+        # Restore the original URL
+        automate_context.automation_run_data.speckle_server_url = original_url

Utilities/utilities.py → src/Utilities/utilities.py

@@ -1,9 +1,9 @@
-from typing import List, TypeVar, Iterable, Optional, Tuple
+from typing import List, TypeVar, Iterable, Optional
 
 from specklepy.objects.base import Base
 import sys
 
-from Utilities.flatten import extract_base_and_transform
+from src.Utilities.flatten import extract_base_and_transform
 
 T = TypeVar("T", bound=Base)
 

main.py → src/main.py

@@ -1,16 +1,17 @@
-"""This module contains the business logic for a Speckle Automate function.
+(
+    """This module contains the business logic for a Speckle Automate function.
 
-The purpose is to demonstrate how one can use the automation_context module
-to process and analyze data in a Speckle project.
-"""
+    The purpose is to demonstrate how one can use the automation_context module
+    to process and analyze data in a Speckle project.
+    """
+)
 from pydantic import Field
 from speckle_automate import (
     AutomateBase,
     AutomationContext,
     execute_automate_function,
 )
 
-import Objects.objects
 from Objects.objects import (
     attach_visual_markers,
     colorise_densities,
@@ -25,6 +26,7 @@
 ## swap those into the original commit object
 ## send that back to the server
 
+
 class FunctionInputs(AutomateBase):
     """Definition of user inputs for this function.
 
@@ -53,7 +55,7 @@ class FunctionInputs(AutomateBase):
 
 
 def automate_function(
-        automate_context: AutomationContext, function_inputs: FunctionInputs
+    automate_context: AutomationContext, function_inputs: FunctionInputs
 ) -> None:
     """Analyzes Speckle data and provides visual markers and notifications.
 
@@ -84,6 +86,10 @@ def automate_function(
         automate_context, health_objects, function_inputs.density_level
     )
 
+
+
+
+
     colorise_densities(automate_context, health_objects)
 
     # Wrap up the analysis by marking the run either successful or failed.
@@ -95,7 +101,9 @@ def automate_function(
 
     commit_details = {
         "stream_id": automate_context.automation_run_data.project_id,
-        "commit_id": automate_context.automation_run_data.triggers[0].payload.version_id,
+        "commit_id": automate_context.automation_run_data.triggers[
+            0
+        ].payload.version_id,
         "server_url": automate_context.automation_run_data.speckle_server_url,
     }
 
@@ -117,12 +125,12 @@ def automate_function(
 
     file_name = Report.write_pdf_to_temp(report)
 
-    print(commit_details['server_url'])
+    print(commit_details["server_url"])
 
     automate_context.store_file_result(file_name)
 
     # colorise the objects that pass/fail and send to a new model version
-    Objects.objects.transport_recolorized_commit(
+    src.Objects.objects.transport_recolorized_commit(
         automate_context, health_objects, version_root_object
     )
 

tests/conftest.py

@@ -1,5 +1,8 @@
 import os
+import sys
 from dotenv import load_dotenv
+# Add the src directory to the Python path
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../src')))
 
 
 def pytest_configure(config):

tests/test_function.py

@@ -14,7 +14,7 @@
 from specklepy.api.client import SpeckleClient
 from specklepy.objects.base import Base
 
-from main import FunctionInputs, automate_function
+from src.main import FunctionInputs, automate_function
 
 
 def crypto_random_string(length: int) -> str:
@@ -94,7 +94,6 @@ def test_object() -> Base:
     return root_object
 
 
-
 @pytest.fixture()
 # fixture to mock the AutomationRunData that would be generated by a full Automation Run
 def fake_automation_run_data(request, test_client: SpeckleClient) -> AutomationRunData:

tests/test_helpers.py

@@ -1,8 +1,8 @@
 import pytest
 from specklepy.objects.base import Base
 
-from Objects.objects import HealthObject
-from Utilities.utilities import Utilities
+from src.Objects import HealthObject
+from src.Utilities import Utilities
 
 
 @pytest.fixture
@@ -39,7 +39,7 @@ def test_filter_displayable_bases(mock_base):
     displayable_bases = Utilities.filter_displayable_bases(mock_base)
     assert (
         len(displayable_bases) == 2
-    )  # Only child_1 and child_2 should be considered displayable
+    )
 
 
 def test_convert_from_base_with_nested_elements(mock_base):
@@ -48,7 +48,7 @@ def test_convert_from_base_with_nested_elements(mock_base):
     assert health_obj.id == "12345"
     assert (
         health_obj.speckle_type == "Base"
-    )  # Assuming no speckle_type was set in the mock_base
+    )
 
 
 def test_density_with_nested_elements(mock_base):

tests/test_local.py

@@ -2,13 +2,13 @@
 from typing import Any
 
 import pytest
-
 # Speckle is a data platform for AEC; here we're importing essential modules from it
 from specklepy.api import operations
 from specklepy.api.client import SpeckleClient
 from specklepy.objects import Base
 from specklepy.transports.server import ServerTransport
 
+
 # Setting up some pytest fixtures for testing
 # Fixtures are a way to provide consistent test data or configuration for each test
 

tests/test_utilities.py

@@ -2,7 +2,7 @@
 from specklepy.objects.base import Base
 from specklepy.objects.geometry import Mesh
 
-from Utilities.utilities import Utilities
+from src.Utilities import Utilities
 
 
 @pytest.fixture