Bump actions/checkout from 4.2.2 to 6.0.2

Bumps [actions/checkout](https://github.com/actions/checkout) from 4.2.2 to 6.0.2.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4.2.2...v6.0.2)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: 6.0.2
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

.devcontainer/Dockerfile

@@ -0,0 +1,30 @@
+# Use the official Python 3.13 slim image as the base
+FROM python:3.13-slim
+
+# Change to UK mirror for better reliability (robust for missing files)
+RUN find /etc/apt/ -name '*.list' -exec sed -i 's|http://deb.debian.org|http://ftp.uk.debian.org|g' {} + || true
+
+# Force apt to use IPv4 to avoid CDN/network issues
+RUN echo 'Acquire::ForceIPv4 "true";' > /etc/apt/apt.conf.d/99force-ipv4
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+  git \
+  && rm -rf /var/lib/apt/lists/*
+
+# Set the working directory
+WORKDIR /home/speckle
+
+# Create a non-root user
+RUN useradd -ms /bin/bash vscode
+USER vscode
+
+# Set environment variables
+ENV PYTHONPATH=/home/speckle
+ENV PYTHONUNBUFFERED=1
+
+# Install Python dependencies
+COPY requirements.txt requirements-dev.txt pyproject.toml ./
+RUN pip install --no-cache-dir -r requirements.txt && \
+  pip install --no-cache-dir -r requirements-dev.txt && \
+  echo 'export PATH=$PATH:$HOME/.local/bin' >> ~/.bashrc 

.devcontainer/devcontainer.json

@@ -1,43 +1,49 @@
-// For format details, see https://aka.ms/devcontainer.json. For config options, see the
-// README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
-  "name": "Python 3",
-  // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
-  "image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye",
-  "features": {
-    "ghcr.io/devcontainers-contrib/features/poetry:2": {}
-  },
-
-  "remoteEnv": {
-    "SPECKLE_TOKEN": "foobar"
-  },
-  "containerEnv": {
-    "SPECKLE_TOKEN": "asdfasdf"
-  },
-
-  // Features to add to the dev container. More info: https://containers.dev/features.
-  // "features": {},
-
-  // Use 'forwardPorts' to make a list of ports inside the container available locally.
-  // "forwardPorts": [],
-
-  // Use 'postCreateCommand' to run commands after the container is created.
-  "postCreateCommand": "cp .env.example .env && POETRY_VIRTUALENVS_IN_PROJECT=true poetry install --no-root",
-
-  // Configure tool-specific properties.
+  "name": "Model Checker - An Automate Function",
+  "dockerFile": "Dockerfile",
+  "context": "..",
+  "workspaceFolder": "/home/speckle",
+  "runArgs": [
+    "--network",
+    "host"
+  ],
+  "mounts": [
+    "source=${localWorkspaceFolder},target=/home/speckle,type=bind,consistency=cached"
+  ],
   "customizations": {
     "vscode": {
-      // Add the IDs of extensions you want installed when the container is created.
       "extensions": [
-        "ms-python.vscode-pylance",
         "ms-python.python",
+        "ms-python.vscode-pylance",
         "ms-python.black-formatter",
-        "streetsidesoftware.code-spell-checker",
-        "mikestead.dotenv"
-      ]
+        "ms-python.isort",
+        "ms-python.flake8",
+        "littlefoxteam.vscode-python-test-adapter",
+        "ms-azuretools.vscode-docker",
+        "charliermarsh.ruff"
+      ],
+      "settings": {
+        "python.defaultInterpreterPath": "/usr/local/bin/python",
+        "python.linting.enabled": true,
+        "python.linting.flake8Enabled": true,
+        "python.formatting.provider": "black",
+        "python.testing.pytestEnabled": true,
+        "python.testing.unittestEnabled": false,
+        "python.testing.nosetestsEnabled": false,
+        "python.testing.pytestArgs": [
+          "tests"
+        ],
+        "python.testing.autoTestDiscoverOnSaveEnabled": true,
+        "python.testing.cwd": "${workspaceFolder}",
+        "[python]": {
+          "editor.formatOnSave": true,
+          "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+          }
+        }
+      }
     }
-  }
-
-  // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
-  // "remoteUser": "root"
-}
+  },
+  "postCreateCommand": "sh -c \"mkdir -p ~/.pip && echo '[global]\nprefer-ipv4 = true' > ~/.pip/pip.conf\"",
+  "postStartCommand": "echo 'Container started successfully!'"
+}

.github/workflows/main.yml

@@ -13,7 +13,7 @@ jobs:
     steps:
       # Step 1: Checkout the repository
       - name: Checkout Repository
-        uses: actions/checkout@v4.2.2
+        uses: actions/checkout@v6.0.2
 
       # Step 2: Set up Python
       - name: Setup Python
@@ -31,7 +31,9 @@ jobs:
       - name: Extract functionInputSchema
         id: extract_schema
         run: |
-          python main.py generate_schema "${{ env.FUNCTION_SCHEMA_FILE_NAME }}"
+          python main.py generate_schema "${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}"
+          echo "Checking if functionSchema.json exists after generation..."
+          ls -lah "${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}"
 
       # Step 5: Build and publish the Speckle function
       - name: Speckle Automate Function - Build and Publish
@@ -42,3 +44,4 @@ jobs:
           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_recommended_memory_mi: 5000

.idea/misc.xml

@@ -4,4 +4,7 @@
     <option name="sdkName" value="WSL Checker" />
   </component>
   <component name="ProjectRootManager" version="2" project-jdk-name="uv (Checker)" project-jdk-type="Python SDK" />
+  <component name="PythonCompatibilityInspectionAdvertiser">
+    <option name="version" value="3" />
+  </component>
 </project>

.python-version

@@ -1 +1 @@
-3.12
+3.13

.vscode/settings.json

@@ -5,5 +5,27 @@
     "stringcase",
     "typer"
   ],
-  "python.defaultInterpreterPath": ".venv/bin/python"
-}
+  "python.defaultInterpreterPath": ".venv/bin/python",
+  "python.testing.pytestEnabled": true,
+  "python.testing.unittestEnabled": false,
+  "python.testing.nosetestsEnabled": false,
+  "python.testing.pytestArgs": [
+    "tests"
+  ],
+  "python.testing.autoTestDiscoverOnSaveEnabled": true,
+  "python.testing.cwd": "${workspaceFolder}",
+  "editor.formatOnSave": true,
+  "editor.rulers": [
+    79
+  ],
+  "editor.codeActionsOnSave": {
+    "source.organizeImports": "explicit"
+  },
+  "[python]": {
+    "editor.defaultFormatter": "charliermarsh.ruff",
+    "editor.formatOnSave": true,
+    "editor.codeActionsOnSave": {
+      "source.organizeImports.ruff": "explicit"
+    }
+  }
+}

DEVELOPER_README.md

@@ -1,56 +1,377 @@
-# Checker Function Development Guide
+# Checker Function Developer Guide
 
-## Setup
+This document provides technical details for developers working on the Speckle Checker Automate function.
 
-1. Install dependencies:
+## Project Overview
+
+The Checker function enables validation of Speckle objects against user-defined rules in a spreadsheet. It's designed to
+be flexible, supporting various object schemas including both v2 and v3 Speckle APIs.
+
+## Setup Development Environment
+
+### Prerequisites
+
+- Python 3.10+
+- Poetry for dependency management
+
+### Installation
+
+1. Clone the repository
+2. Install dependencies:
+   ```bash
+   poetry install
+   ```
+3. Activate the virtual environment:
+   ```bash
+   poetry shell
+   ```
+
+### Test Automation Environment
+
+The project uses Speckle's [Test Automation feature](https://speckle.guide/automate/function-testing.html) to run
+integration tests against real Speckle data. This provides a sandboxed environment to validate the function's business
+logic without triggering actual automations.
+
+#### Setting Up a Test Automation
+
+1. Navigate to your Speckle project
+2. Go to the **Automations** tab
+3. Click **New Automation**
+4. Select **Create Test Automation** in the bottom left
+5. Follow the configuration steps
+
+Note: To create a test automation, you must:
+
+- Be an owner of the Speckle project
+- Have published this function to the Function Library
+- Have at least one release for the function
+
+#### Environment Configuration
+
+For local integration testing, create a `.env` file in the project root with these variables:
+
+```
+# Your Personal Access Token from Speckle
+SPECKLE_TOKEN=your_speckle_token
+
+# The Speckle server URL
+SPECKLE_SERVER_URL=https://app.speckle.systems
+
+# From the test automation URL: /projects/[project-id]/automations/[automation-id]
+SPECKLE_PROJECT_ID=your_project_id
+SPECKLE_AUTOMATION_ID=your_automation_id
+```
+
+This configuration allows the test suite to:
+
+1. Connect to your test automation via the Speckle API
+2. Run the function locally against real Speckle data
+3. Submit results to the test automation for validation
+
+For detailed instructions, refer to
+the [official documentation on function testing](https://speckle.guide/automate/function-testing.html#how-to-create-a-test-automation).
+
+#### Running Integration Tests
+
+With the `.env` file configured:
 
 ```bash
-poetry shell && poetry install
+# Run the integration tests
+pytest test_function.py
 ```
 
-2. Configure `.env`:
+The SDK utilities will automatically:
 
-```
-SPECKLE_TOKEN=your_speckle_token
-SPECKLE_SERVER_URL=app.speckle.systems
+- Connect to your test automation
+- Execute your function with the specified test data
+- Submit results back to Speckle
+
+Test results will be visible on the automation page in the Speckle UI.
+
+#### Unit Tests
+
+For unit tests that don't require a full Speckle connection, you can run:
+
+```bash
+# Run unit tests only
+pytest test_comparisons.py test_rule_processing.py
 ```
 
-Get test automation details from app.speckle.systems
+Note: The `.env` file should never be committed to version control (it's included in .gitignore)
 
 ## Project Structure
 
-- `function.py`: Main business logic
-- `rules.py`: Rule definitions and processing
-- `inputs.py`: Function input schema
-- `helpers.py`: Utility functions
-- `spreadsheet.py`: TSV handling
+```
+├── main.py                  # Entry point for Automate
+├── src/
+│   ├── function.py          # Main function logic
+│   ├── inputs.py            # Function input schema
+│   ├── helpers.py           # Utility functions
+│   ├── filters.py           # Object filtering functions
+│   ├── rules.py             # Rule definitions and property handling
+│   ├── predicates.py        # Predicate mapping for spreadsheet values
+│   ├── rule_processor.py    # Rule application and result handling
+│   └── spreadsheet.py       # TSV file parsing
+├── tests/
+│   ├── conftest.py          # Test fixtures
+│   ├── test_function.py     # Main function tests
+│   ├── test_comparisons.py  # Value comparison tests
+│   ├── test_parameters.py   # Parameter handling tests
+│   └── test_rule_processing.py  # Rule processing tests
+├── pyproject.toml           # Project dependencies
+└── poetry.lock              # Locked dependencies
+```
+
+## Core Components
+
+### 1. Function Execution Flow
+
+The main execution flow is defined in `function.py`:
+
+1. `automate_function()` receives context and inputs from Automate
+2. Retrieves Speckle objects via `automate_context.receive_version()`
+3. Flattens the object tree using `flatten_base()`
+4. Loads rules from the spreadsheet URL via `read_rules_from_spreadsheet()`
+5. Applies rules to objects using `apply_rules_to_objects()`
+6. Reports results via the Automate context
+
+### 2. Rule Processing
+
+Rules are processed through several stages:
+
+1. **Spreadsheet Parsing** (`spreadsheet.py`):
+    - Reads TSV data
+    - Groups rules by rule number
+    - Validates rule structure
+
+2. **Rule Application** (`rule_processor.py`):
+    - Processes rule logic (WHERE, AND, CHECK)
+    - Evaluates conditions against objects
+    - Attaches results to objects in Automate context
+
+3. **Property Rules** (`rules.py`):
+    - Handles property lookups in objects
+    - Implements comparison logic
+    - Supports both v2 and v3 Speckle schemas
+
+### 3. Property Access System
+
+The system uses a flexible property access mechanism that works with different Speckle schemas:
+
+- **V2 Schema**: Properties in `parameters` dictionary with internal definition names
+- **V3 Schema**: Properties in nested `properties.Parameters` structure
+
+The `PropertyRules` class provides methods to:
+
+- Find properties by path or name
+- Extract values with appropriate type conversion
+- Perform comparisons with tolerance and type handling
+
+## Test-Driven Development for Rules
+
+The test infrastructure is designed to support Test-Driven Development (TDD) when creating new rules or extending
+functionality. This approach is especially powerful for rule development as it allows you to verify behavior against
+known test objects.
+
+### Using Test Fixtures for Rule Development
+
+The `conftest.py` file contains test fixtures that provide sample Speckle objects for testing:
+
+```python
+@pytest.fixture
+def v2_wall():
+    """Creates a v2-style Speckle wall object"""
+    wall = Base()
+    wall.id = "cdb18060dc48281909e94f0f1d8d3cc0"
+    wall.type = "W30(Fc24)"
+    wall.units = "mm"
+    wall.family = "Basic Wall"
+    wall.height = 1400
+    wall.flipped = False
+    wall.category = "Walls"
+    # ... more properties
+
+    return wall
+
+
+@pytest.fixture
+def v3_wall():
+    """Creates a v3-style Speckle wall object"""
+    wall = Base()
+    wall.id = "46f06fef727d64a0bbcbd7ced51e0cd2"
+    wall.name = "Walls - W30(Fc24)"
+    wall.type = "W30(Fc24)"
+    wall.units = "mm"
+    wall.family = "Basic Wall"
+    # ... more properties
+
+    return wall
+```
+
+These fixtures create standardized test objects that represent different Speckle schema versions, allowing you to test
+rule behavior consistently.
+
+### TDD Workflow for New Rules
+
+When developing a new rule or predicate, follow this TDD approach:
+
+1. **Add test fixtures**: First, expand `conftest.py` with representative objects that your rule will process
+
+2. **Write tests first**: Create test cases in a test file (e.g., `test_my_rule.py`):
+   ```python
+   def test_new_wall_rule(v2_wall, v3_wall):
+       """Test a new rule that checks wall thickness requirements"""
+       # Test with v2 schema
+       assert PropertyRules.is_new_wall_check(v2_wall, "width", "300")
+       
+       # Test with v3 schema
+       assert PropertyRules.is_new_wall_check(v3_wall, "Width", "300")
+       
+       # Test failure case
+       v2_wall.parameters["WALL_ATTR_WIDTH_PARAM"].value = 200
+       assert not PropertyRules.is_new_wall_check(v2_wall, "width", "300")
+   ```
+
+3. **Implement the rule**: Add the new rule method to the `PropertyRules` class in `rules.py`:
+   ```python
+   @staticmethod
+   def is_new_wall_check(speckle_object: Base, parameter_name: str, expected_value: str) -> bool:
+       """Checks if a wall meets specific thickness requirements"""
+       parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
+       # Implement rule logic
+       return result
+   ```
+
+4. **Add to predicate mapping**: Register your new rule in `predicates.py`:
+   ```python
+   PREDICATE_METHOD_MAP = {
+       # Existing predicates...
+       "new_wall_check": PropertyRules.is_new_wall_check.__name__,
+   }
+   ```
+
+5. **Run tests to verify**:
+   ```bash
+   pytest test_my_rule.py -v
+   ```
+
+### Creating Comprehensive Test Objects
+
+For the most effective testing, your test objects in `conftest.py` should:
+
+1. **Include diverse objects**: Walls, columns, beams, etc.
+2. **Cover edge cases**: Null values, missing properties, special characters
+3. **Represent both schemas**: Include both v2 and v3 format objects
+4. **Include real-world examples**: Extract sample objects from actual projects
+
+You can extract real objects for testing using:
+
+```python
+# Example code to extract and save real objects for test fixtures
+from specklepy.api import operations
+from specklepy.api.client import SpeckleClient
+from specklepy.transports.server import ServerTransport
+
+client = SpeckleClient(host="app.speckle.systems")
+client.authenticate_with_token(token)
+
+transport = ServerTransport(client=client, stream_id="stream_id")
+obj = operations.receive("object_id", transport)
+
+# Print structure to help with fixture creation
+print(obj.get_member_names())
+print(obj.get_dynamic_member_names())
+```
+
+By following this TDD approach and maintaining comprehensive test fixtures, you can develop robust rules that work
+reliably across different object schemas and handle edge cases appropriately.
 
 ## Testing
 
+### Running Tests
+
 ```bash
-poetry run pytest
+# Run all tests
+pytest
+
+# Run specific test file
+pytest tests/test_parameters.py
+
+# Run with coverage
+pytest --cov=src
 ```
 
-## Extending Rules
+### Test Data
 
-1. Add new predicate to `input_predicate_mapping` in `rules.py`
-2. Create corresponding method in `PropertyRules` class
-3. Update tests
+Test fixtures in `conftest.py` provide sample objects:
 
-## Building
+- `v2_wall`: Wall object in v2 schema
+- `v3_wall`: Wall object in v3 schema
 
-The function is packaged as a Docker container:
+### Manual Testing with Real Data
 
-```bash
-docker build -f ./Dockerfile -t checker .
-```
+For testing with real Speckle data:
 
-## Local Testing
+```python
+from specklepy.api import operations
+from specklepy.api.client import SpeckleClient
+from specklepy.api.credentials import get_account_from_token
+from specklepy.transports.server import ServerTransport
 
-```bash
-docker run --rm checker python -u main.py run [automation_data] [parameters] [token]
+client = SpeckleClient(host="app.speckle.systems")
+account = get_account_from_token(token, "app.speckle.systems")
+client.authenticate_with_account(account)
+
+transport = ServerTransport(client=client, stream_id="your_stream_id")
+commit = client.commit.get(stream_id="your_stream_id", commit_id="your_commit_id")
+obj = operations.receive(commit.referencedObject, transport)
 ```
 
 ## Deployment
 
-Create a GitHub release to trigger deployment to Speckle Automate.
+The function is deployed through GitHub Actions:
+
+1. Create a GitHub release to trigger the build workflow
+2. The workflow builds the necessary artifacts and pushes them to the Speckle Automate registry
+3. The function becomes available in the Speckle Automate UI
+
+## Performance Considerations
+
+- **Large Object Trees**: When processing large models, use aggressive filtering with WHERE clauses
+- **Rule Complexity**: Minimize the number of nested property lookups
+- **Memory Usage**: Be aware of object reference handling and avoid deep copies
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Rule not matching expected objects**:
+    - Check property paths for the specific object type
+    - Verify data types (strings vs. numbers)
+    - Enable debug logging
+
+2. **Slow performance**:
+    - Check for inefficient property lookups
+    - Add more specific WHERE filters to reduce object set
+
+3. **Docker build failures**:
+    - Check dependency compatibility
+    - Verify Python version requirements
+
+## Contributing
+
+1. Create a branch for your feature or fix
+2. Add tests for new functionality
+3. Update documentation
+4. Submit a pull request
+5. Ensure CI tests pass
+
+## Future Development
+
+Potential improvements:
+
+- Support for more complex rule logic (OR conditions)
+- UI-based rule editor
+- Result visualization tools
+- Performance optimizations for large models
+- Support for referencing other objects in rules

Dockerfile

@@ -1,16 +1,15 @@
-# We use the official Python 3.11 image as our base image and will add our code to it. For more details, see https://hub.docker.com/_/python
+# Use the official Python 3.13 slim image as the base
 FROM python:3.13-slim
 
-# We install poetry to generate a list of dependencies which will be required by our application
-RUN pip install poetry==1.8.4
-
-# We set the working directory to be the /home/speckle directory; all of our files will be copied here.
+# Set the working directory inside the container
 WORKDIR /home/speckle
 
-# Copy all of our code and assets from the local directory into the /home/speckle directory of the container.
-# We also ensure that the user 'speckle' owns these files, so it can access them
-# This assumes that the Dockerfile is in the same directory as the rest of the code
+# Copy the application files to the working directory
 COPY . /home/speckle
 
-# Using poetry, we generate a list of requirements, save them to requirements.txt, and then use pip to install them
-RUN poetry export --format requirements.txt --output /home/speckle/requirements.txt && pip install --requirement /home/speckle/requirements.txt
+# Upgrade pip and install dependencies using requirements.txt
+RUN pip install --no-cache-dir --upgrade pip && \
+  pip install --no-cache-dir -r /home/speckle/requirements.txt
+
+# Set the entrypoint for running the Speckle function
+CMD ["python", "-u", "main.py", "run"]

README.md

@@ -1,36 +1,130 @@
-# Public Function: Checker
+# Model Checker
 
-Validate Speckle objects against configurable rules using spreadsheet definitions.
+Model Checker is an Automate function that validates Speckle objects against configurable rules. This approach provides
+a flexible way to implement quality checks and maintain consistent standards across projects.
 
-## Usage
+## Overview
 
-1. Access the template Google Sheet [link needed]
-2. Make a copy to your Google Drive using File > Make a copy
-3. Define your rules in your sheet
-4. Click "Speckle" menu > "Publish Rules" to get your TSV URL
-5. Create an Automation in Speckle Automate using the Checker function
-6. Paste your TSV URL into the function configuration
-7. Run your automation
+The Model Checker allows you to:
 
-## Rule Types
+- Define validation rules for your objects
+- Configure severity levels for issues
+- Check properties across different types of objects
+- Generate reports of validation results
+- Apply consistent standards across projects
 
-- Property existence
-- Value matching
-- Numeric comparisons
-- Range checks
-- List membership
-- Pattern matching
-- Boolean checks
+## Getting Started
 
-## Severity Levels
+### 1. Access the Model Checker Application
 
-- WARNING: Issues that should be reviewed
-- ERROR: Critical issues requiring attention
+1. Go to the [Model Checker Application](https://model-checker.speckle.systems)
+2. Sign in with your Speckle account
+3. Create and manage your validation rules through the intuitive web interface
+
+### 2. Create an Automation
+
+1. Go to your workspace project in [Speckle](https://app.speckle.systems/)
+2. Create a new Automation
+3. Select the Model Checker function
+4. Configure the function:
+    - Set minimum severity level to report
+    - Configure other options as needed
+5. Save and run your automation
+
+## Rule Definition Format
+
+Rules are defined with the following components:
+
+| Logic | Property Name | Predicate    | Value     | Message              | Report Severity |
+|-------|---------------|--------------|-----------|----------------------|-----------------|
+| WHERE | category      | matches      | Walls     | Wall thickness check | ERROR           |
+| CHECK | Width         | greater than | 200       |                      |                 |
+| WHERE | category      | matches      | Columns   | Column height check  | WARNING         |
+| AND   | height        | in range     | 2500,4000 |                      |                 |
+
+### Component Explanation
+
+- **Logic**: Defines how conditions are combined (WHERE, AND, CHECK)
+- **Property Name**: The object property or parameter to check
+- **Predicate**: Comparison operation (equals, greater than, etc.)
+- **Value**: Reference value for comparison
+- **Message**: Description shown in validation results
+- **Report Severity**: ERROR, WARNING, or INFO
+
+### Supported Predicates
+
+| Predicate        | Description                 | Example                               |
+|------------------|-----------------------------|---------------------------------------|
+| exists           | Checks if a property exists | `height` exists                       |
+| equal to         | Exact value match           | `width` equal to `300`                |
+| not equal to     | Value doesn't match         | `material` not equal to `Concrete`    |
+| greater than     | Value exceeds threshold     | `height` greater than `3000`          |
+| less than        | Value below threshold       | `thickness` less than `50`            |
+| in range         | Value within bounds         | `elevation` in range `0,10000`        |
+| in list          | Value in allowed set        | `type` in list `W1,W2,W3`             |
+| contains         | Property contains substring | `name` contains `Beam`                |
+| does not contain | Property doesn't contain    | `name` does not contain `temp`        |
+| is true          | Boolean property is true    | `is_structural` is true               |
+| is false         | Boolean property is false   | `is_placeholder` is false             |
+| is like          | Loose text matching         | `name` is like `Wall` matches `Walls` |
+
+## Rule Logic
+
+- **WHERE**: Filters objects to check (like SELECT WHERE in SQL)
+- **AND**: Additional filter conditions
+- **CHECK**: Final check condition (optional, defaults to last AND)
+
+Objects pass a rule when they match all conditions. Objects that match WHERE/AND filters but fail the CHECK condition
+are reported as issues.
+
+## Working with Object Properties
+
+The Model Checker understands properties in Speckle objects regardless of schema:
+
+- Direct properties: `category`, `name`, `id`
+- Nested properties: `parameters.WIDTH.value`
+- Revit parameters: Use parameter names like `Mark`, `Width`, `Assembly Code`
 
 ## Example Rules
 
-[Screenshot or example table to be added]
+### Wall Thickness Check
+
+```
+Rule: WHERE category equals "Walls" AND width less than "200"
+Message: "Walls must have width of at least 200."
+Severity: ERROR
+```
+
+### Door Naming Convention
+
+```
+Rule: WHERE category equals "Doors" AND name is not like "^D\d{3}$"
+Message: "All doors must have a name that follows the format "D" followed by three digits."
+Severity: WARNING
+```
+
+### Structural Column Height Range
+
+```
+Rule: WHERE category equals "Columns" AND is_structural is true AND height not in range "2400,4000"
+Message: "Structural columns must have a height between 2400 and 4000."
+Severity: ERROR
+```
 
 ## Support
 
-For issues or questions, please open a GitHub issue.
+For issues or questions, please let us know on the [Speckle Community Forum](https://speckle.community/).
+
+### Alternative: TSV File Format
+
+While the Model Checker Application is the recommended way to create and manage rules, you can also create compatible
+TSV (Tab-Separated Values) files manually. This can be useful for:
+
+- Programmatically generating rules
+- Version controlling rules in a text format
+- Integrating with existing workflows
+- Creating rules in bulk
+
+The TSV file should follow the same structure as shown in the table above, with columns separated by tabs. The file will
+then need to be hosted somewhere and served with MIME-type of `text/tab-separated-values` and the URL used in the
+automation configuration.

pyproject.toml

@@ -1,41 +1,57 @@
 [project]
 name = "speckle-automate-checker"
-version = "0.1.0"
+version = "3.0.0"
 description = "Allows for QAQC property checking with Speckle"
-authors = ["Jonathon Broughton <jonathon@speckle.systems>"]
+authors = [{ name = "Jonathon Broughton", email = "jonathon@speckle.systems" }]
 readme = "README.md"
-requires-python = ">=3.12"
+requires-python = ">=3.13"
 dependencies = [
-    "more-itertools>=10.6.0",
-    "pandas>=2.2.3",
-    "pydantic==2.10.6",
-    "python-dotenv>=1.0.1",
-    "python-levenshtein>=0.26.1",
-    "specklepy>=2.21.2",
+  "more-itertools>=10.6.0",
+  "pandas>=2.2.3",
+  "pydantic==2.10.6",
+  "python-dotenv>=1.0.1",
+  "python-levenshtein>=0.26.1",
+  "specklepy>=3.0.0",
+  "pydantic-settings>=2.7.1",
 ]
 
 
-[dependency-groups]
+[project.optional-dependencies]
 dev = [
-    "pytest-assertcount>=1.0.0",
-    "black>=25.1.0",
-    "mypy>=1.15.0",
-    "pydantic-settings>=2.7.1",
-    "pytest>=8.3.4",
-    "ruff>=0.9.6",
+  "mypy>=1.15.0",
+  "pytest>=8.3.4",
+  "pytest-assertcount>=1.0.0",
+  "ruff==0.11.12",
 ]
 
-
 [tool.ruff]
 select = [
-    "E", # pycodestyle
-    "F", # pyflakes
-    "UP", # pyupgrade
-    "D", # pydocstyle
-    "I", # isort
+  "E",  # pycodestyle
+  "F",  # pyflakes
+  "UP", # pyupgrade
+  "D",  # pydocstyle
+  "I",  # isort
 ]
-line-length = 120
-ignore = ["F401", "F403"]
+ignore = ["F401", "F403", "E501"]
+exclude = [".venv", "**/*.yml"]
+line-length = 79
 
 [tool.ruff.pydocstyle]
 convention = "google"
+
+[tool.ruff.format]
+quote-style = "double"
+indent-style = "space"
+line-ending = "auto"
+docstring-code-format = true
+docstring-code-line-length = 79
+
+[tool.ruff.isort]
+known-first-party = ["src"]
+
+
+[tool.ruff.lint.pydocstyle]
+convention = "google"
+
+[tool.setuptools]
+py-modules = []

requirements-dev.txt

@@ -0,0 +1,23 @@
+argcomplete==3.6.2
+click==8.1.8
+colorama==0.4.6
+coverage==7.8.2
+flake8==7.2.0
+iniconfig==2.1.0
+isort==6.0.1
+mccabe==0.7.0
+mypy_extensions==1.1.0
+packaging==24.2
+pathspec==0.12.1
+pipx==1.7.1
+platformdirs==4.3.7
+pluggy==1.6.0
+pycodestyle==2.13.0
+pyflakes==3.3.2
+Pygments==2.19.1
+pytest>=8.3.4
+pytest-assertcount>=1.0.0
+pytest-cov==6.1.1
+ruff==0.11.12
+userpath==1.9.2
+mypy>=1.15.0

requirements.txt

@@ -1,54 +1,7 @@
-annotated-types==0.7.0
-anyio==4.8.0
-appdirs==1.4.4
-attrs==23.2.0
-backoff==2.2.1
-black==25.1.0
-certifi==2025.1.31
-charset-normalizer==3.4.1
-click==8.1.8
-colorama==0.4.6
-deprecated==1.2.18
-gql==3.5.0
-graphql-core==3.2.6
-h11==0.14.0
-httpcore==1.0.7
-httpx==0.25.2
-idna==3.10
-iniconfig==2.0.0
-levenshtein==0.26.1
-more-itertools==10.6.0
-multidict==6.1.0
-mypy==1.15.0
-mypy-extensions==1.0.0
-numpy==2.2.3
-packaging==24.2
-pandas==2.2.3
-pathspec==0.12.1
-platformdirs==4.3.6
-pluggy==1.5.0
-propcache==0.2.1
+more-itertools>=10.6.0
+pandas>=2.2.3
 pydantic==2.10.6
-pydantic-core==2.27.2
-pydantic-settings==2.7.1
-pytest==8.3.4
-pytest-assertcount==1.0.0
-python-dateutil==2.9.0.post0
-python-dotenv==1.0.1
-python-levenshtein==0.26.1
-pytz==2025.1
-rapidfuzz==3.12.1
-requests==2.32.3
-requests-toolbelt==1.0.0
-ruff==0.9.6
-six==1.17.0
-sniffio==1.3.1
-specklepy==2.21.3
-stringcase==1.2.0
-typing-extensions==4.12.2
-tzdata==2025.1
-ujson==5.10.0
-urllib3==2.3.0
-websockets==11.0.3
-wrapt==1.17.2
-yarl==1.18.3
+python-dotenv>=1.0.1
+python-levenshtein>=0.26.1
+specklepy>=3.0.0
+pydantic-settings>=2.7.1

scripts/update-requirements.sh

@@ -0,0 +1,22 @@
+#!/bin/sh
+
+# Store the current Python environment
+CURRENT_ENV=$(pip freeze)
+
+# Remove dev dependencies
+pip uninstall -y pytest pytest-cov isort flake8 ruff
+
+# Generate production requirements
+pip freeze > requirements.txt
+
+# Reinstall dev dependencies
+pip install pytest pytest-cov isort flake8 ruff
+
+# Generate dev requirements
+pip freeze > requirements-dev.txt
+
+# Restore the original environment
+pip uninstall -y pytest pytest-cov isort flake8 ruff
+echo "$CURRENT_ENV" | pip install -r /dev/stdin
+
+echo "Requirements files have been updated successfully!" 

speckle-automate-checker.code-workspace

@@ -0,0 +1,12 @@
+{
+  "folders": [
+    {
+      "path": "."
+    }
+  ],
+  "settings": {
+    "files.autoSave": "onFocusChange",
+    "editor.defaultFormatter": null,
+    "editor.formatOnSave": true
+  }
+}

src/function.py

@@ -1,12 +1,23 @@
-# This is the main function that will be executed when the automation is triggered.
-# It will receive the inputs from the user, and the context of the run.
-# It will then apply the rules to the objects in the model, and report back the results.
+"""This is the main entry point for the Speckle Automate function.
+
+The Speckle Automate system works as follows:
+1. When a model is committed to Speckle, it triggers automations associated with the project
+2. For each automation, Speckle Automate prepares a runtime environment and context
+3. The automation context includes the model data and function inputs
+4. This function is executed to process the model and provide results
+5. Results are attached to objects in the model, creating an annotated view
+
+This function implements a configurable rule-based validation system that:
+- Reads validation rules from an external spreadsheet
+- Applies these rules to objects in the Speckle model
+- Reports validation results back to the Speckle platform
+- Provides an annotated view of the model showing validation issues
+"""
 
-from pandas import DataFrame
 from speckle_automate import AutomationContext
 from specklepy.objects.base import Base
 
-from src.helpers import flatten_base
+from src.helpers import flatten_base, speckle_print
 from src.inputs import FunctionInputs
 from src.rule_processor import apply_rules_to_objects
 from src.spreadsheet import read_rules_from_spreadsheet
@@ -18,41 +29,98 @@ def automate_function(
     automate_context: AutomationContext,
     function_inputs: FunctionInputs,
 ) -> None:
-    """This VERSION of the function will add a check for the new provide inputs.
+    """Main entry point for the Speckle Automate function.
+
+    This function is called by the Speckle Automate system when the automation is triggered.
+    It orchestrates the entire validation process:
+
+    1. Receiving and flattening the model data
+    2. Detecting the Speckle object schema version
+    3. Loading and grouping rules from the external spreadsheet
+    4. Applying rules to objects and collecting results
+    5. Reporting results back to the Speckle platform
 
     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.
+        automate_context: A context helper provided by Speckle Automate that:
+            - Provides access to the Speckle model data
+            - Handles result reporting and view management
+            - Manages run status (success, failure, exception)
+        function_inputs: User-provided inputs defined in the FunctionInputs schema,
+            particularly the URL to the rules spreadsheet
     """
-    # the context provides a convenient way, to receive the triggering VERSION
+    # -------------------------------------------------------------------------
+    # Step 1: Receive and process the model data
+    # -------------------------------------------------------------------------
+
+    # The AutomationContext provides a convenient way to access the model data
+    # that triggered this automation run
     version_root_object: Base = automate_context.receive_version()
 
-    # We can continue to work with a flattened list of objects.
+    # Flatten the object tree into a list of objects
+    # The Speckle object model is hierarchical, but for validation purposes,
+    # it's easier to work with a flat list of objects
     flat_list_of_objects = list(flatten_base(version_root_object))
 
-    # If it is a next_gen model, we can get the VERSION from the root object
-    # This function's rules don't make use of this check, but it is here for reference if you want to.
+    # -------------------------------------------------------------------------
+    # Step 2: Detect Speckle object schema version
+    # -------------------------------------------------------------------------
+
+    # The Speckle object schema has evolved over time
+    # In newer models, we can detect the version from the root object
+    # This version information helps our validation logic handle different schemas
     global VERSION
     VERSION = getattr(version_root_object, "version", 2)  # noqa: F841SION = getattr(version_root_object,"version", 2)  # noqa: F841  # noqa: F841
 
-    # read the rules from the spreadsheet
-    rules: DataFrame = read_rules_from_spreadsheet(function_inputs.spreadsheet_url)
+    # In v2, parameters are stored in a 'parameters' dictionary on each object
+    # In v3, they are nested in 'properties.Parameters' with categorization
+    speckle_print(f"Detected Speckle object schema version: {VERSION}")
 
-    if (rules is None) or (len(rules) == 0):
-        automate_context.mark_run_exception("No rules defined")
+    # -------------------------------------------------------------------------
+    # Step 3: Load and process rules from the spreadsheet
+    # -------------------------------------------------------------------------
 
-    grouped_rules = rules.groupby("Rule Number")
+    # The rules are defined in an external spreadsheet (TSV format)
+    # This allows non-technical users to define and modify rules
+    # without changing the code
+    grouped_rules, messages = read_rules_from_spreadsheet(
+        function_inputs.spreadsheet_url
+    )
 
-    # apply the rules to the objects
-    apply_rules_to_objects(flat_list_of_objects, grouped_rules, automate_context)
+    # Handle any validation messages from rule processing
+    for message in messages:
+        speckle_print(message)  # or log them appropriately
 
-    # set the automation context view, to the original model / VERSION view
+    # If rule processing failed, mark the run as failed and exit
+    if grouped_rules is None:
+        automate_context.mark_run_exception("Failed to process rules")
+        return
+
+    # -------------------------------------------------------------------------
+    # Step 4: Apply rules to objects and collect results
+    # -------------------------------------------------------------------------
+
+    # This is where the actual validation happens
+    # Each rule is applied to relevant objects, and results are collected
+    # Results are attached to objects in the model to create an annotated view
+    apply_rules_to_objects(
+        flat_list_of_objects,
+        grouped_rules,
+        automate_context,
+        minimum_severity=function_inputs.minimum_severity,
+        hide_skipped=function_inputs.hide_skipped,
+    )
+
+    # -------------------------------------------------------------------------
+    # Step 5: Finalize the automation run
+    # -------------------------------------------------------------------------
+
+    # Set the context view to the original model/version view
+    # This ensures that the results are displayed in the correct context
     automate_context.set_context_view()
 
-    # report success
+    # Mark the run as successful and provide a summary message
+    # This message will be displayed to the user in the Speckle UI
     automate_context.mark_run_success(
-        f"Successfully applied {len(grouped_rules)} rules to {len(flat_list_of_objects)} version {VERSION} objects."
+        f"Successfully applied {len(grouped_rules)} rules to "
+        f"{len(flat_list_of_objects)} version {VERSION} objects."
     )

src/helpers.py

@@ -4,7 +4,7 @@ from collections.abc import Generator, Iterable
 from typing import Any
 
 from specklepy.objects import Base
-from specklepy.objects.other import Instance, Transform
+from specklepy.objects.proxies import InstanceProxy as Instance
 
 
 def speckle_print(log_string: str = "banana") -> None:
@@ -27,7 +27,8 @@ def get_item(obj: Base | dict[str, Any], key, default=None):
         return obj.get(key, default)
     elif hasattr(obj, key):  # If it's an object with the attribute
         return getattr(obj, key, default)
-    return default  # Return default if it's neither a dict nor an object with the attribute
+    return default  # Return default if it's neither a dict nor an object with
+    # the attribute
 
 
 def has_item(obj: Base | dict[str, Any], key: str) -> bool:
@@ -39,7 +40,9 @@ def has_item(obj: Base | dict[str, Any], key: str) -> bool:
     return False
 
 
-def flatten_base_thorough(base: Base, parent_type: str = None) -> Iterable[Base]:
+def flatten_base_thorough(
+    base: Base, parent_type: str | None = None
+) -> Iterable[Base]:
     """Take a base and flatten it to an iterable of bases.
 
     Args:
@@ -69,7 +72,9 @@ def flatten_base_thorough(base: Base, parent_type: str = None) -> Iterable[Base]
                 print(category)
                 if category.startswith("@"):
                     category_object: Base = getattr(base, category)[0]
-                    yield from flatten_base_thorough(category_object, category_object.speckle_type)
+                    yield from flatten_base_thorough(
+                        category_object, category_object.speckle_type
+                    )
 
         except KeyError:
             pass
@@ -80,52 +85,78 @@ def flatten_base_thorough(base: Base, parent_type: str = None) -> Iterable[Base]
 def extract_base_and_transform(
     base: Base,
     inherited_instance_id: str | None = None,
-    transform_list: list[Transform] | None = None,
+    transform_list: list[list[float]] | None = None,
 ) -> Generator[
-    Base | str | list[Transform] | None | tuple[Base, Any | None, list[Transform] | None | list[Any]], Any | None, None
+    Base
+    | str
+    | list[list[float]]
+    | None
+    | tuple[Base, Any | None, list[list[float]] | None | list[Any]],
+    Any | None,
 ]:
-    """Traverses Speckle object hierarchies to yield `Base` objects and their transformations.
+    """Traverses Speckle object hierarchies to yield `Base`s and transformas.
 
-    Tailored to Speckle's AEC data structures, it covers the newer hierarchical structures
-    with Collections and also  with patterns found in older Revit specific data.
+    Tailored to Speckle's AEC data structures, it covers the newer
+    hierarchical structures with Collections and also  with patterns found in
+    older Revit specific data.
 
     Parameters:
     - base (Base): The starting point `Base` object for traversal.
-    - inherited_instance_id (str, optional): The inherited identifier for `Base` objects without a unique ID.
-    - transform_list (List[Transform], optional): Accumulated list of transformations from parent to child objects.
+    - inherited_instance_id (str, optional): The inherited identifier for
+      `Base` objects without a unique ID.
+    - transform_list (List[List[float]], optional): Accumulated list of
+      transformations from parent to child objects.
 
     Yields:
-    - tuple: A `Base` object, its identifier, and a list of applicable `Transform` objects or None.
+    - tuple: A `Base` object, its identifier, and a list of applicable
+      transformations or None.
 
-    The id of the `Base` object is either the inherited identifier for a definition from an instance
-    or the one defined in the object.
+    The id of the `Base` object is either the inherited identifier for a
+    definition from an instance or the one defined in the object.
     """
-    # Derive the identifier for the current `Base` object, defaulting to an inherited one if needed.
+    # Derive the identifier for the current `Base` object, defaulting to an
+    # inherited one if needed.
     current_id = getattr(base, "id", inherited_instance_id)
     transform_list = transform_list or []
 
     if isinstance(base, Instance):
-        # Append transformation data and dive into the definition of `Instance` objects.
+        # Append transformation data and dive into the definition of `Instance`
+        # objects.
         if base.transform:
             transform_list.append(base.transform)
         if base.definition:
-            yield from extract_base_and_transform(base.definition, current_id, transform_list.copy())
+            yield from extract_base_and_transform(
+                base.definition, current_id, transform_list.copy()
+            )
     else:
         # Initial yield for the current `Base` object.
         yield base, current_id, transform_list
 
-        # Process 'elements' and '@elements', typical containers for `Base` objects in AEC models.
-        elements_attr = getattr(base, "elements", []) or getattr(base, "@elements", [])
+        # Process 'elements' and '@elements', typical containers for `Base`
+        # objects in AEC models.
+        elements_attr = getattr(base, "elements", []) or getattr(
+            base, "@elements", []
+        )
         for element in elements_attr:
             if isinstance(element, Base):
-                # Recurse into each `Base` object within 'elements' or '@elements'.
-                yield from extract_base_and_transform(element, current_id, transform_list.copy())
+                # Recurse into each `Base` object within 'elements' or
+                # '@elements'.
+                yield from extract_base_and_transform(
+                    element, current_id, transform_list.copy()
+                )
 
-        # Recursively process '@'-prefixed properties that are Base objects with 'elements'.
-        # This is a common pattern in older Speckle data models, such as those used for Revit commits.
+        # Recursively process '@'-prefixed properties that are Base objects
+        # with 'elements'.
+        # This is a common pattern in older Speckle data models, such as those
+        # used for Revit commits.
         for attr_name in dir(base):
             if attr_name.startswith("@"):
                 attr_value = getattr(base, attr_name)
-                # If the attribute is a Base object containing 'elements', recurse into it.
-                if isinstance(attr_value, Base) and hasattr(attr_value, "elements"):
-                    yield from extract_base_and_transform(attr_value, current_id, transform_list.copy())
+                # If the attribute is a Base object containing 'elements',
+                # recurse into it.
+                if isinstance(attr_value, Base) and hasattr(
+                    attr_value, "elements"
+                ):
+                    yield from extract_base_and_transform(
+                        attr_value, current_id, transform_list.copy()
+                    )

src/inputs.py

@@ -1,3 +1,8 @@
+"""This file contains the inputs for the function.
+
+It is used to define the inputs for the function and to validate them.
+"""
+
 from enum import Enum
 
 from pydantic import Field
@@ -5,9 +10,20 @@ from speckle_automate import AutomateBase
 
 
 class PropertyMatchMode(Enum):
-    STRICT = "strict" # Exact parameter path match
-    FUZZY = "fuzzy"   # Search all parameters ignoring hierarchy
-    MIXED = "mixed"   # Exact match first, fuzzy fallback
+    """Controls how strictly parameter names must match."""
+
+    STRICT = "strict"  # Exact parameter path match
+    FUZZY = "fuzzy"  # Search all parameters ignoring hierarchy
+    MIXED = "mixed"  # Exact match first, fuzzy fallback
+
+
+class MinimumSeverity(str, Enum):
+    """Enum for minimum severity level to report."""
+
+    INFO = "Info"
+    WARNING = "Warning"
+    ERROR = "Error"
+
 
 class FunctionInputs(AutomateBase):
     """These are function author defined values.
@@ -17,23 +33,29 @@ class FunctionInputs(AutomateBase):
     https://docs.pydantic.dev/latest/usage/models/
     """
 
-
-
-
-
-
-
     # In this exercise, we will move rules to an external source so not to hardcode them.
     spreadsheet_url: str = Field(
         title="Spreadsheet URL",
         description="This is the URL of the spreadsheet to check. It should be a TSV format data source.",
     )
 
-    property_match_mode: PropertyMatchMode = Field(
-        default=PropertyMatchMode.MIXED,
-        title="Property Match Mode",
-        description='Controls how strictly parameter names must match. ' +
-                    'STRICT will only match exact parameter paths, ' +
-                    'FUZZY will search all parameters ignoring hierarchy, ' +
-                    'MIXED will exact match first, fuzzy fallback.'
+    minimum_severity: MinimumSeverity = Field(
+        default=MinimumSeverity.INFO,
+        title="Minimum Severity Level",
+        description="Only report test results with this severity level or higher. Info will show all results, Warning will show warnings and errors, Error will show only errors.",
     )
+
+    hide_skipped: bool = Field(
+        default=False,
+        title="Hide Skipped Tests",
+        description="If enabled, tests that were skipped (no matching objects found) will not be reported.",
+    )
+
+    # property_match_mode: PropertyMatchMode = Field(
+    #     default=PropertyMatchMode.MIXED,
+    #     title="Property Match Mode",
+    #     description='Controls how strictly parameter names must match. ' +
+    #                 'STRICT will only match exact parameter paths, ' +
+    #                 'FUZZY will search all parameters ignoring hierarchy, ' +
+    #                 'MIXED will exact match first, fuzzy fallback.'
+    # )

src/predicates.py

@@ -1,19 +1,22 @@
-"""Configuration module defining mappings between spreadsheet predicates and rule methods."""
+"""Defines mappings between spreadsheet predicates and rule methods."""
 
 from src.rules import PropertyRules
 
 # Mapping of input predicates to the corresponding methods in PropertyRules
 PREDICATE_METHOD_MAP = {
     "exists": PropertyRules.has_parameter.__name__,
-    "matches": PropertyRules.is_parameter_value.__name__,
     "greater than": PropertyRules.is_parameter_value_greater_than.__name__,
     "less than": PropertyRules.is_parameter_value_less_than.__name__,
     "in range": PropertyRules.is_parameter_value_in_range.__name__,
     "in list": PropertyRules.is_parameter_value_in_list.__name__,
     "equal to": PropertyRules.is_equal_value.__name__,
+    "not equal to": PropertyRules.is_not_equal_value.__name__,
     "is true": PropertyRules.is_parameter_value_true.__name__,
     "is false": PropertyRules.is_parameter_value_false.__name__,
     "is like": PropertyRules.is_parameter_value_like.__name__,
     "identical to": PropertyRules.is_identical_value.__name__,
-    "not equal": PropertyRules.is_not_equal_value.__name__,
+    "contains": PropertyRules.is_parameter_value_containing.__name__,
+    "does not contain": (
+        PropertyRules.is_parameter_value_not_containing.__name__
+    ),
 }

src/rule_processor.py

@@ -1,3 +1,18 @@
+"""Module for processing rules against Speckle objects and updating the automate context with the results.
+
+This module implements the core rule processing logic that:
+1. Validates rule structure and logic
+2. Evaluates rule conditions against Speckle objects
+3. Separates filtering conditions and final check conditions
+4. Processes rule groups and tracks results
+5. Reports results back to the Speckle Automate context
+
+The rule processing follows a "filter then validate" approach:
+- Filter conditions (WHERE, AND) narrow down which objects to check
+- The final check condition (CHECK or last AND) determines pass/fail
+"""
+
+import json
 from enum import Enum
 from typing import Any
 
@@ -7,91 +22,230 @@ from speckle_automate import AutomationContext, ObjectResultLevel
 from specklepy.objects.base import Base
 
 from src.helpers import speckle_print
+from src.inputs import MinimumSeverity
 from src.predicates import PREDICATE_METHOD_MAP
 from src.rules import PropertyRules
 
 
-def evaluate_condition(
-    speckle_object: Base, condition: pd.Series, rule_number: str | None = None, case_number: int | None = None
-) -> bool:
-    """Given a Speckle object and a condition, evaluates the condition and returns a boolean value.
+def validate_rule_structure(rule_group: pd.DataFrame) -> None:
+    """Validates the structure and logic of a rule group.
 
-    A condition is a pandas Series object with the following keys:
-    - 'Property Name': The name of the property to evaluate.
-    - 'Predicate': The predicate to use for evaluation.
-    - 'Value': The value to compare against.
+    This ensures the rule follows the proper format:
+    - First condition must be WHERE
+    - Following conditions can be AND
+    - Only one CHECK condition is allowed (and must be last)
 
     Args:
-        rule_number (string): For information the rule number.
-        case_number (int): For information the rule clause number.
-        speckle_object (Base): The Speckle object to evaluate.
-        condition (pd.Series): The condition to evaluate.
+        rule_group: DataFrame containing the rule conditions
+
+    Raises:
+        ValueError: If rule structure is invalid
+    """
+    if rule_group.empty:
+        return
+
+    # Validate Logic column exists
+    if "Logic" not in rule_group.columns:
+        raise ValueError("Rule must have a 'Logic' column")
+
+    # Get uppercase Logic values for case-insensitive comparison
+    logic_values = rule_group["Logic"].str.upper()
+
+    # Check if first condition is WHERE
+    if logic_values.iloc[0] != "WHERE":
+        raise ValueError(
+            f"Rule {rule_group.iloc[0]['Rule Number']} must start with WHERE"
+        )
+
+    # Count CHECK conditions
+    check_count = sum(1 for value in logic_values if value == "CHECK")
+    if check_count > 1:
+        raise ValueError(
+            f"Rule {rule_group.iloc[0]['Rule Number']} has multiple CHECK conditions"
+        )
+
+    # If CHECK exists, ensure it's the last condition
+    check_indices = logic_values[logic_values == "CHECK"].index
+    if check_count == 1 and check_indices[0] != rule_group.index[-1]:
+        raise ValueError(
+            f"CHECK must be the last condition in rule {rule_group.iloc[0]['Rule Number']}"
+        )
+
+    # Validate Logic values
+    valid_values = {"WHERE", "AND", "CHECK"}
+    invalid_values = set(logic_values.unique()) - valid_values
+    if invalid_values:
+        raise ValueError(f"Invalid Logic values found: {invalid_values}")
+
+
+def evaluate_condition(
+    speckle_object: Base,
+    condition: pd.Series,
+    rule_number: str | None = None,
+    case_number: int | None = None,
+) -> bool:
+    """Evaluates a single condition against a Speckle object.
+
+    This function is the bridge between the rules defined in the spreadsheet
+    and the property checking methods in PropertyRules. It:
+    1. Extracts the property name, predicate, and value from the condition
+    2. Maps the predicate to the corresponding method in PropertyRules
+    3. Calls the method with the object, property name, and value
+
+    Args:
+        speckle_object: The Speckle object to evaluate against
+        condition: A pandas Series containing the condition details
+            - 'Property Name': The name of the property to check
+            - 'Predicate': The comparison operation (like 'equals',
+                           'greater than')
+            - 'Value': The value to compare against
+        rule_number: For tracking, the rule number being evaluated
+        case_number: For tracking, the condition number within the rule
 
     Returns:
-        bool: The result of the evaluation. True if the condition is met, False otherwise.
+        True if the condition is met, False otherwise
     """
-    property_name = condition["Property Name"]
+    property_name = condition.get(
+        "Property Name", condition.get("Property Path")
+    )
     predicate_key = condition["Predicate"]
     value = condition["Value"]
 
+    # Debugging info
     _ = rule_number
     _ = case_number
 
+    # Look up the method name in the predicate map
+    # This map connects spreadsheet predicates to PropertyRules methods
     if predicate_key in PREDICATE_METHOD_MAP:
         method_name = PREDICATE_METHOD_MAP[predicate_key]
         method = getattr(PropertyRules, method_name, None)
 
         if method:
-            check_answer = method(speckle_object, property_name, value)
+            # Call the method with the object, property name, and value
+            return method(speckle_object, property_name, value)
 
-            return check_answer
     return False
 
 
+def get_filters_and_check(
+    rule_group: pd.DataFrame,
+) -> tuple[pd.DataFrame, pd.Series]:
+    """Separates rule conditions into filtering conditions and the final check condition.
+
+    This function handles two rule formats:
+    1. Explicit format: WHERE + AND... + CHECK
+    2. Legacy format: WHERE + AND... (last AND is implicitly the check)
+
+    This separation enables the "filter then validate" approach.
+
+    Args:
+        rule_group: DataFrame containing rule conditions
+
+    Returns:
+        Tuple containing (filter_conditions, final_check_condition)
+    """
+    if rule_group.empty:
+        return pd.DataFrame(), pd.Series()
+
+    # Get uppercase Logic values for case-insensitive comparison
+    logic_values = rule_group["Logic"].str.upper()
+
+    # Look for explicit CHECK
+    check_conditions = rule_group[logic_values == "CHECK"]
+    has_explicit_check = not check_conditions.empty
+
+    if has_explicit_check:
+        # Use first CHECK condition as final check
+        final_check = check_conditions.iloc[0]
+        # All other conditions are filters
+        filters = rule_group[logic_values != "CHECK"]
+    else:
+        # Legacy behavior: use last AND as check if present
+        and_conditions = rule_group[logic_values == "AND"]
+        if not and_conditions.empty:
+            # Get the last AND as the check
+            final_check = and_conditions.iloc[-1]
+            # All conditions up to the last AND are filters
+            last_and_idx = and_conditions.index[-1]
+            filters = rule_group[rule_group.index < last_and_idx]
+        else:
+            # No AND conditions found, just use WHERE as filter
+            filters = rule_group
+            final_check = rule_group.iloc[
+                0
+            ]  # Default to first condition as check
+
+    return filters, final_check
+
+
 def process_rule(
     speckle_objects: list[Base], rule_group: pd.DataFrame
 ) -> tuple[list[Any], list[Any]] | tuple[list[Base], list[Base]]:
-    """Processes a set of rules against Speckle objects, returning those that pass and fail.
+    """Processes a rule group against a list of Speckle objects.
 
-    The first rule is used as a filter ('WHERE'), and subsequent rules as conditions ('AND').
+    This function implements the "filter then validate" approach:
+    1. Apply filter conditions sequentially to narrow down objects
+    2. Apply the final check condition to determine pass/fail
+
+    This approach is efficient for large models as it reduces the number
+    of objects that need full validation.
 
     Args:
-        speckle_objects: List of Speckle objects to be processed.
-        rule_group: DataFrame defining the filter and conditions.
+        speckle_objects: List of Speckle objects to be processed
+        rule_group: DataFrame defining the filter and check conditions
 
     Returns:
-        A tuple of lists containing objects that passed and failed the rule.
+        A tuple of lists (pass_objects, fail_objects)
     """
-    # Extract the 'WHERE' condition and subsequent 'AND' conditions
-    filter_condition = rule_group.iloc[0]
-    subsequent_conditions = rule_group.iloc[1:]
-
-    # get the last row of the rule_group and get the Message and Report Severity
-    rule_info = rule_group.iloc[-1]
-    rule_number = rule_info["Rule Number"]
-
-    # Filter objects based on the 'WHERE' condition
-    filtered_objects = [
-        speckle_object for speckle_object in speckle_objects if evaluate_condition(speckle_object, filter_condition)
-    ]
-
-    if not filtered_objects or len(list(filtered_objects)) == 0:
+    if not speckle_objects or rule_group.empty:
         return [], []
 
-    # Initialize lists for passed and failed objects
-    pass_objects, fail_objects = [], []
+    try:
+        validate_rule_structure(rule_group)
+    except ValueError as e:
+        speckle_print(f"Rule validation error: {str(e)}")
+        return [], []
 
-    # Evaluate each filtered object against the 'AND' conditions
-    for speckle_object in filtered_objects:
-        if all(
-            evaluate_condition(
-                speckle_object=speckle_object, condition=condition, rule_number=rule_number, case_number=index
+    # Get filters and final check
+    filters, final_check = get_filters_and_check(rule_group)
+
+    # Start with all objects
+    filtered_objects = speckle_objects.copy()
+    rule_number = rule_group.iloc[0]["Rule Number"]
+
+    #  Apply each filter condition sequentially
+    for index, (_, filter_condition) in enumerate(filters.iterrows()):
+        filtered_objects = [
+            obj
+            for obj in filtered_objects
+            if evaluate_condition(
+                speckle_object=obj,
+                condition=filter_condition,
+                rule_number=rule_number,
+                case_number=index,
             )
-            for index, condition in subsequent_conditions.iterrows()
+        ]
+
+        # Early exit if no objects pass filters
+        if not filtered_objects:
+            return [], []
+
+    # For remaining objects, evaluate the final check
+    # This separates objects into pass/fail groups
+    pass_objects = []
+    fail_objects = []
+
+    for obj in filtered_objects:
+        if evaluate_condition(
+            speckle_object=obj,
+            condition=final_check,
+            rule_number=rule_number,
+            case_number=len(filters),
         ):
-            pass_objects.append(speckle_object)
+            pass_objects.append(obj)
         else:
-            fail_objects.append(speckle_object)
+            fail_objects.append(obj)
 
     return pass_objects, fail_objects
 
@@ -100,40 +254,97 @@ def apply_rules_to_objects(
     speckle_objects: list[Base],
     grouped_rules: DataFrameGroupBy,
     automate_context: AutomationContext,
+    minimum_severity: MinimumSeverity = MinimumSeverity.INFO,
+    hide_skipped: bool = False,
 ) -> dict[str, tuple[list[Base], list[Base]]]:
-    """Applies defined rules to a list of objects and updates the automate context based on the results.
+    """Applies rules to objects and updates the automate context results.
+
+    This is the main orchestration function that:
+    1. Processes each rule group against all objects
+    2. Filters results based on severity levels
+    3. Attaches results to objects in the Speckle Automate context
+    4. Reports skipped rules (where no objects matched filters)
 
     Args:
-        speckle_objects (List[Base]): The list of objects to which rules are applied.
-        grouped_rules (pd.DataFrameGroupBy): The DataFrame containing rule definitions.
-        automate_context (Any): Context manager for attaching rule results.
+        speckle_objects: The list of objects to which rules are applied
+        grouped_rules: The rules grouped by rule number
+        automate_context: Context manager for attaching results to objects
+        minimum_severity: Minimum severity level to report
+        hide_skipped: Whether to hide skipped rules in results
+
+    Returns:
+        Dictionary mapping rule IDs to (pass_objects, fail_objects) tuples
     """
     grouped_results = {}
-
     rules_processed = 0
+    severity_levels = {
+        MinimumSeverity.INFO: 0,
+        MinimumSeverity.WARNING: 1,
+        MinimumSeverity.ERROR: 2,
+    }
+    min_severity_level = severity_levels[minimum_severity]
 
     for rule_id, rule_group in grouped_rules:
         rule_id_str = str(rule_id)  # Convert rule_id to string
-
         rules_processed += 1
 
         # Ensure rule_group has necessary columns
-        if "Message" not in rule_group.columns or "Report Severity" not in rule_group.columns:
+        if "Message" not in rule_group.columns or (
+            "Report Severity" not in rule_group.columns
+            and "Severity" not in rule_group.columns
+        ):
             continue  # Or raise an exception if these columns are mandatory
 
+        # Get the severity level for this rule
+        rule_severity = get_severity(rule_group.iloc[-1])
+        rule_severity_level = severity_levels[
+            MinimumSeverity(rule_severity.value)
+        ]
+
+        # Check if the rule severity level meets the minimum severity level
+        # no point in processing lower severity rules
+        if rule_severity_level < min_severity_level:
+            continue
+
         pass_objects, fail_objects = process_rule(speckle_objects, rule_group)
 
-        attach_results(pass_objects, rule_group.iloc[-1], rule_id_str, automate_context, True)
-        attach_results(fail_objects, rule_group.iloc[-1], rule_id_str, automate_context, False)
+        # For passing objects, only attach if we're showing all levels (INFO)
+        if minimum_severity == MinimumSeverity.INFO:
+            attach_results(
+                pass_objects,
+                rule_group.iloc[-1],
+                rule_id_str,
+                automate_context,
+                True,
+            )
+
+        # For failing objects, attach if they meet minimum severity threshold
+        if len(fail_objects) and rule_severity_level >= min_severity_level:
+            attach_results(
+                fail_objects,
+                rule_group.iloc[-1],
+                rule_id_str,
+                automate_context,
+                False,
+            )
+
+        if (
+            len(pass_objects) == 0
+            and len(fail_objects) == 0
+            and not hide_skipped
+        ):
+            speckle_print(f"Rule {rule_id_str} Skipped")
+
+            newBase = Base()
+            newBase.id = "123"
 
-        if len(pass_objects) == 0 and len(fail_objects) == 0:
             automate_context.attach_info_to_objects(
                 category=f"Rule {rule_id_str} Skipped",
-                object_ids=["0"],  # This is a hack to get a rule to report with no valid objects
+                affected_objects=[newBase],
+                # This is a hack to get a rule to report with no valid objects
                 message=f"No objects found for rule {rule_id_str}",
                 metadata={},
             )
-            # pass
 
         grouped_results[rule_id_str] = (pass_objects, fail_objects)
 
@@ -142,7 +353,13 @@ def apply_rules_to_objects(
 
 
 class SeverityLevel(Enum):
-    """Enum for severity levels."""
+    """Enumeration for severity levels of rule results.
+
+    These severity levels determine how rule failures are displayed:
+    - INFO: Informational, no action required
+    - WARNING: Potential issue that should be reviewed
+    - ERROR: Critical issue requiring attention
+    """
 
     INFO = "Info"
     WARNING = "Warning"
@@ -150,21 +367,33 @@ class SeverityLevel(Enum):
 
 
 def get_severity(rule_info: pd.Series) -> SeverityLevel:
-    """Convert a string severity level to the corresponding SeverityLevel enum.
+    """Convert a string severity to the corresponding SeverityLevel enum.
 
-    This function normalizes input strings (because processing user entered dead is hard), handling:
+    This function normalizes user input with robust handling for:
     - Case insensitivity (e.g., "info", "WARNING" → "Info", "Warning")
     - Shorthand mappings (e.g., "WARN" → "Warning")
-    - Stripping whitespace
-    - Defaults to SeverityLevel.ERROR if the input is invalid
-    """
-    severity = rule_info.get("Report Severity")  # Extract severity from input data
+    - Whitespace handling
+    - Default fallback to ERROR for invalid input
 
-    # If severity is None or not a string (e.g., numeric input), default to ERROR
+    Args:
+        rule_info: Series containing rule information with 'Report Severity'
+                   key
+
+    Returns:
+        Appropriate SeverityLevel enum value
+    """
+    severity = rule_info.get("Report Severity") or rule_info.get(
+        "Severity"
+    )  # Extract severity from input data
+
+    # If severity is None or not a string (e.g., numeric input),
+    # default to ERROR
     if not isinstance(severity, str):
         return SeverityLevel.ERROR
 
-    severity = severity.strip().upper()  # Remove leading/trailing spaces & normalize case
+    severity = (
+        severity.strip().upper()
+    )  # Remove leading/trailing spaces & normalize case
 
     # Define a mapping for shorthand or alternate spellings
     alias_map = {
@@ -174,7 +403,8 @@ def get_severity(rule_info: pd.Series) -> SeverityLevel:
     # Replace shorthand values if applicable
     severity = alias_map.get(severity, severity)
 
-    # Attempt to match with an existing SeverityLevel enum value (case-insensitive)
+    # Attempt to match with an existing SeverityLevel enum value
+    # (case-insensitive)
     return next(
         (level for level in SeverityLevel if level.value.upper() == severity),
         SeverityLevel.ERROR,  # Default to ERROR if no match is found
@@ -182,17 +412,45 @@ def get_severity(rule_info: pd.Series) -> SeverityLevel:
 
 
 def get_metadata(
-    rule_id: str, rule_info: pd.Series, passed: bool, speckle_objects: list[Base]
+    rule_id: str,
+    rule_info: pd.Series,
+    passed: bool,
+    speckle_objects: list[Base],
 ) -> dict[str, str | int | Any]:
-    """Function that generates metadata with severity validation."""
-    metadata = {
-        "rule_id": rule_id,
-        "status": "PASS" if passed else "FAIL",
-        "severity": get_severity(rule_info).value,  # Keep proper casing
-        "rule_message": rule_info["Message"],
-        "object_count": len(speckle_objects),
-    }
-    return metadata
+    """Generates structured metadata for rule results.
+
+    This metadata is attached to objects in the Speckle platform and is:
+    1. Validated for JSON serializability
+    2. Structured for consistent representation
+    3. Includes key information about the rule and results
+
+    Args:
+        rule_id: Identifier for the rule
+        rule_info: Series containing rule information
+        passed: Boolean indicating if the rule passed
+        speckle_objects: List of Speckle objects affected
+
+    Returns:
+        Dictionary containing metadata if valid JSON serializable,
+          empty dict otherwise
+    """
+    try:
+        metadata = {
+            "rule_id": rule_id,
+            "status": "PASS" if passed else "FAIL",
+            "severity": get_severity(rule_info).value,
+            "rule_message": format_message(rule_info),
+            "object_count": len(speckle_objects),
+        }
+
+        # Validate JSON serializability
+        json.dumps(metadata)
+        return metadata
+
+    except (TypeError, ValueError, json.JSONDecodeError) as e:
+        # Log the error for debugging purposes
+        print(f"Error creating metadata: {str(e)}")
+        return {}
 
 
 def attach_results(
@@ -202,14 +460,20 @@ def attach_results(
     context: AutomationContext,
     passed: bool,
 ) -> None:
-    """Attaches the results of a rule to the objects in the context.
+    """Attaches rule results to objects in the Speckle Automate context.
+
+    This function is the interface to the Speckle platform for reporting
+    results:
+    - For failing objects, attaches results with appropriate severity levels
+    - For passing objects, attaches informational results
+    - Includes structured metadata for consistent reporting
 
     Args:
-        speckle_objects (List[Base]): The list of objects to which the rule was applied.
-        rule_info (pd.Series): The information about the rule.
-        rule_id (str): The ID of the rule.
-        context (AutomationContext): The context manager for attaching results.
-        passed (bool): Whether the rule passed or failed.
+        speckle_objects: The list of objects affected by the rule
+        rule_info: Information about the rule
+        rule_id: Identifier for the rule
+        context: The Speckle Automate context for result attachment
+        passed: Whether the objects passed the rule
     """
     if not speckle_objects:
         return
@@ -217,8 +481,7 @@ def attach_results(
     # Create structured metadata for onward data analysis uses
 
     metadata = get_metadata(rule_id, rule_info, passed, speckle_objects)
-
-    message = f"{rule_info['Message']}"
+    message = format_message(rule_info)
 
     if not passed:
         speckle_print(rule_info["Report Severity"])
@@ -230,7 +493,7 @@ def attach_results(
         )
         context.attach_result_to_objects(
             category=f"Rule {rule_id}",
-            object_ids=[speckle_object.id for speckle_object in speckle_objects],
+            affected_objects=speckle_objects,
             message=message,
             level=severity,
             metadata=metadata,
@@ -238,7 +501,27 @@ def attach_results(
     else:
         context.attach_info_to_objects(
             category=f"Rule {rule_id}",
-            object_ids=[speckle_object.id for speckle_object in speckle_objects],
+            affected_objects=speckle_objects,
             message=message,
             metadata=metadata,
         )
+
+
+def format_message(rule_info):
+    """Format the message for the rule result.
+
+    Handles cases where the message might be None or NaN.
+
+    Args:
+        rule_info: Series containing rule information with 'Message' key
+
+    Returns:
+        Formatted message string
+    """
+    message = (
+        str(rule_info["Message"])
+        if rule_info["Message"] is not None
+        and not pd.isna(rule_info["Message"])
+        else "No Message"
+    )
+    return message

src/rules.py

@@ -1,3 +1,16 @@
+"""A collection of rules for processing Speckle objects and their properties.
+
+This module provides essential utilities for:
+1. Accessing and comparing properties across different Speckle object versions (v2/v3)
+2. Handling nested property paths with a flexible search mechanism
+3. Converting between different value types (strings, booleans, numbers)
+4. Implementing various comparison predicates for validation rules
+
+The core challenge addressed by this module is the evolving schema of Speckle objects.
+In v2, parameters were stored directly in a 'parameters' dictionary, while in v3,
+they are nested within a more complex 'properties.Parameters' structure with categories.
+"""
+
 import math
 import re
 from typing import Any
@@ -9,13 +22,30 @@ PRIMITIVE_TYPES = (bool, int, float, str, type(None))
 
 
 class Rules:
-    """A collection of rules for processing properties in Speckle objects."""
+    """A collection of rules for processing properties in Speckle objects.
+
+    This class provides utilities for working with displayable objects
+    in the Speckle ecosystem.
+    """
 
     @staticmethod
     def try_get_display_value(
         speckle_object: Base,
     ) -> list[Base] | None:
-        """Try fetching the display value from a Speckle object."""
+        """Try fetching the display value from a Speckle object.
+
+        Speckle objects might store display geometry in various ways:
+        - 'displayValue' (newer versions)
+        - '@displayValue' (older versions)
+
+        This method handles both cases transparently.
+
+        Args:
+            speckle_object: The Speckle object to extract display value from
+
+        Returns:
+            List of Base objects representing display geometry, or None if not found
+        """
         raw_display_value = getattr(speckle_object, "displayValue", None) or getattr(
             speckle_object, "@displayValue", None
         )
@@ -32,7 +62,21 @@ class Rules:
 
     @staticmethod
     def is_displayable_object(speckle_object: Base) -> bool:
-        """Determines if a given Speckle object is displayable."""
+        """Determines if a given Speckle object is displayable.
+
+        A Speckle object is considered displayable if:
+        1. It has an ID and displayable geometry, OR
+        2. It has a definition with an ID and displayable geometry
+           (typically for instanced objects)
+
+        This is useful for filtering out non-visible/utility objects.
+
+        Args:
+            speckle_object: The Speckle object to check
+
+        Returns:
+            True if the object is displayable, False otherwise
+        """
         display_values = Rules.try_get_display_value(speckle_object)
         if display_values and getattr(speckle_object, "id", None) is not None:
             return True
@@ -47,7 +91,17 @@ class Rules:
 
     @staticmethod
     def get_displayable_objects(flat_list_of_objects: list[Base]) -> list[Base]:
-        """Filters a list of Speckle objects to only include displayable objects."""
+        """Filters a list of Speckle objects to only include displayable objects.
+
+        This is useful when processing a flattened object tree but only wanting
+        to work with objects that have visual representation.
+
+        Args:
+            flat_list_of_objects: A list of Speckle objects to filter
+
+        Returns:
+            A filtered list containing only displayable objects with IDs
+        """
         return [
             speckle_object
             for speckle_object in flat_list_of_objects
@@ -56,18 +110,99 @@ class Rules:
 
 
 class PropertyRules:
-    """A collection of rules for processing parameters in Speckle objects."""
+    """A collection of rules for processing parameters in Speckle objects.
+
+    This class provides the core functionality for:
+    - Locating properties in complex object hierarchies
+    - Converting between different value types
+    - Comparing values with appropriate type handling
+    - Implementing various comparison predicates for validation rules
+
+    It's designed to work with both Speckle v2 and v3 object schemas.
+    """
+
+    @staticmethod
+    def is_parameter_value_not_containing(speckle_object: Base, parameter_name: str, substring: str) -> bool:
+        """Checks if parameter value does not contain the given substring.
+
+        This is the logical inverse of is_parameter_value_containing.
+
+        Args:
+           speckle_object: The Speckle object to check
+           parameter_name: Name of the parameter to check
+           substring: The substring to look for
+
+        Returns:
+           True if the parameter value does not contain the substring
+        """
+        # Invert the result of contains check
+        return not PropertyRules.is_parameter_value_containing(speckle_object, parameter_name, substring)
+
+    @staticmethod
+    def is_parameter_value_containing(speckle_object: Base, parameter_name: str, substring: str) -> bool:
+        """Checks if parameter value contains the given substring.
+
+        Case-insensitive substring matching for parameters.
+        If the parameter doesn't exist, returns False.
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: Name of the parameter to check
+            substring: The substring to look for
+
+        Returns:
+            True if the parameter value contains the substring
+        """
+        parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
+        if parameter_value is None:
+            return False
+
+        # Convert both to strings for comparison
+        try:
+            parameter_str = str(parameter_value).lower()
+            substring_str = str(substring).lower()
+            return substring_str in parameter_str
+        except (TypeError, ValueError) as e:
+            print(f"Error in is_parameter_value_contains: {e}")
+            return False
 
     @staticmethod
     def normalize_path(path: str) -> str:
-        """Remove technical path prefixes like 'properties' and 'parameters'."""
+        """Remove technical path prefixes like 'properties' and 'parameters'.
+
+        This helps make property paths version-agnostic by focusing on the
+        meaningful parts of the path rather than the container structure.
+
+        Examples:
+        - 'properties.Parameters.Type Parameters.Construction.Width' becomes 'Type Parameters.Construction.Width'
+        - 'parameters.WALL_ATTR_WIDTH_PARAM' becomes 'WALL_ATTR_WIDTH_PARAM'
+
+        Args:
+            path: The parameter path to normalize
+
+        Returns:
+            A normalized path with technical prefixes removed
+        """
         parts = path.split(".")
         filtered = [p for p in parts if p.lower() not in ("properties", "parameters")]
         return ".".join(filtered)
 
     @staticmethod
     def convert_revit_boolean(value: Any) -> Any:
-        """Convert Revit-style Yes/No strings to boolean values."""
+        """Convert Revit-style Yes/No strings to boolean values.
+
+        Revit and some other BIM applications use "Yes"/"No" strings
+        instead of boolean values. This function converts them:
+        - "Yes" → True
+        - "No" → False
+        - Other values remain unchanged
+
+        Args:
+            value: The value to potentially convert
+
+        Returns:
+            Converted boolean if applicable, otherwise original value
+        """
         # Handle None case
         if value is None:
             return None
@@ -89,7 +224,20 @@ class PropertyRules:
 
     @staticmethod
     def get_obj_value(obj: Any, get_raw: bool = False) -> Any:
-        """Extract appropriate value from an object, handling special cases."""
+        """Extract appropriate value from an object, handling special cases.
+
+        This function handles the various ways values might be stored:
+        - In v2 Parameter objects (with .value property)
+        - In v3 dictionary structures (with 'value' key)
+        - As primitive values directly
+
+        Args:
+            obj: The object to extract value from
+            get_raw: If True, return the object itself without extracting value
+
+        Returns:
+            The extracted value, possibly with Yes/No conversion
+        """
         if get_raw:
             return obj
 
@@ -113,7 +261,19 @@ class PropertyRules:
 
     @staticmethod
     def search_obj(obj: Any, parts: list[str]) -> tuple[bool, Any]:
-        """Recursively search an object following a path."""
+        """Recursively search an object following a path.
+
+        This is a key part of the property access mechanism, allowing
+        navigation through nested object structures using dot notation.
+        The search is case-insensitive to handle inconsistencies.
+
+        Args:
+            obj: The object to search within
+            parts: List of path components to follow
+
+        Returns:
+            Tuple of (found: bool, value: Any)
+        """
         if not parts:
             return True, obj
 
@@ -142,6 +302,14 @@ class PropertyRules:
     def find_property(root: Any, search_path: str, get_raw: bool = False) -> tuple[bool, Any]:
         """Find a property by searching through nested objects.
 
+        This method implements a flexible property search that:
+        1. First attempts a direct path match
+        2. Then recursively searches through nested object structures
+        3. Uses cycle detection to prevent infinite recursion
+
+        The approach handles both v2 and v3 Speckle object schemas and
+        supports fuzzy property matching by normalizing paths.
+
         Args:
             root: The root object to search
             search_path: Path to the property to find
@@ -199,7 +367,17 @@ class PropertyRules:
 
     @staticmethod
     def has_parameter(speckle_object: Base, parameter_name: str, *_args, **_kwargs) -> bool:
-        """Check if a parameter exists in the Speckle object."""
+        """Check if a parameter exists in the Speckle object.
+
+        This method is version-agnostic and works with both v2 and v3 objects.
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to look for
+
+        Returns:
+            True if parameter exists, False otherwise
+        """
         found, _ = PropertyRules.find_property(speckle_object, parameter_name)
         return found
 
@@ -210,29 +388,58 @@ class PropertyRules:
         default_value: Any = None,
         get_raw: bool = False,
     ) -> Any:
-        """Get a parameter value from the Speckle object using strict path matching.
+        """Get a parameter value from the Speckle object using path matching.
+
+        This is the core property access method that:
+        1. Handles both v2 and v3 object structures
+        2. Supports direct and nested property paths
+        3. Applies appropriate value extraction and conversion
 
         Args:
             speckle_object: The Speckle object to search
-            parameter_name: Exact parameter path to find
+            parameter_name: Parameter path to find
             default_value: Value to return if parameter not found
             get_raw: Whether to return raw values without conversion
 
         Returns:
-            The parameter value if found using exact path matching, otherwise default_value
+            The parameter value if found, otherwise default_value
         """
         found, value = PropertyRules.find_property(speckle_object, parameter_name, get_raw)
         return value if found else default_value
 
     @staticmethod
     def is_parameter_value(speckle_object: Base, parameter_name: str, value_to_match: Any) -> bool:
-        """Checks if the value of the specified parameter matches the given value."""
+        """Checks if the value of the specified parameter matches the given value.
+
+        This is a basic equality check that leverages the parameter access system.
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+            value_to_match: The value to compare against
+
+        Returns:
+            True if values match, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         return parameter_value == value_to_match
 
     @staticmethod
     def parse_number_from_string(input_string: str):
-        """Attempts to parse a number from a string."""
+        """Attempts to parse a number from a string.
+
+        First tries to parse as integer, then as float if that fails.
+        Raises ValueError if the string is not a valid number.
+
+        Args:
+            input_string: The string to parse
+
+        Returns:
+            int or float value
+
+        Raises:
+            ValueError: If the string is not a valid number
+        """
         try:
             return int(input_string)
         except ValueError:
@@ -243,27 +450,77 @@ class PropertyRules:
 
     @staticmethod
     def is_parameter_value_greater_than(speckle_object: Base, parameter_name: str, threshold: str) -> bool:
-        """Checks if parameter value is greater than threshold."""
+        """Checks if parameter value is greater than threshold.
+
+        This implements the 'greater than' predicate for numeric comparisons.
+
+        Note: From a UX perspective, if someone writes 'height greater than 2401',
+        they mean "flag an error if height <= 2401". So we implement the check to match
+        that intuitive interpretation.
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+            threshold: The threshold value as a string
+
+        Returns:
+            True if parameter value > threshold, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         if parameter_value is None:
             return False
-        if not isinstance(parameter_value, int | float):
-            raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
+        try:
+            parameter_value = float(parameter_value)
+        except (ValueError, TypeError):
+            return False  # Return False if the value cannot be converted to a number
         return parameter_value > PropertyRules.parse_number_from_string(threshold)
 
     @staticmethod
     def is_parameter_value_less_than(speckle_object: Base, parameter_name: str, threshold: str) -> bool:
-        """Checks if parameter value is less than threshold."""
+        """Checks if parameter value is less than threshold.
+
+        This implements the 'less than' predicate for numeric comparisons.
+
+        Note: From a UX perspective, if someone writes 'height less than 2401',
+        they mean "flag an error if height >= 2401". So we implement the check to match
+        that intuitive interpretation.
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+            threshold: The threshold value as a string
+
+        Returns:
+            True if parameter value < threshold, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         if parameter_value is None:
             return False
-        if not isinstance(parameter_value, int | float):
-            raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
+        try:
+            parameter_value = float(parameter_value)
+        except (ValueError, TypeError):
+            return False  # Return False if the value cannot be converted to a number
+
         return parameter_value < PropertyRules.parse_number_from_string(threshold)
 
     @staticmethod
     def is_parameter_value_in_range(speckle_object: Base, parameter_name: str, value_range: str) -> bool:
-        """Checks if parameter value falls within range."""
+        """Checks if parameter value falls within specified range.
+
+        This implements the 'in range' predicate for numeric comparisons.
+        The range is specified as "min,max" and is inclusive.
+
+        Note: From a UX perspective, if someone writes 'height in range 2401,3000',
+        they mean "flag an error if height < 2401 or height > 3000".
+
+        Args:
+           speckle_object: The Speckle object to check
+           parameter_name: The parameter name/path to check
+           value_range: Range specification as "min,max"
+
+        Returns:
+           True if min <= parameter value <= max, False otherwise
+        """
         min_value, max_value = value_range.split(",")
         min_value = PropertyRules.parse_number_from_string(min_value)
         max_value = PropertyRules.parse_number_from_string(max_value)
@@ -271,8 +528,10 @@ class PropertyRules:
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         if parameter_value is None:
             return False
-        if not isinstance(parameter_value, int | float):
-            raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
+        try:
+            parameter_value = float(parameter_value)
+        except (ValueError, TypeError):
+            return False  # Return False if the value cannot be converted to a number
 
         return min_value <= parameter_value <= max_value
 
@@ -284,7 +543,22 @@ class PropertyRules:
         fuzzy: bool = False,
         threshold: float = 0.8,
     ) -> bool:
-        """Checks if parameter value matches pattern."""
+        """Checks if parameter value matches pattern.
+
+        This implements the 'is like' predicate with two modes:
+        1. Regular expression matching (fuzzy=False)
+        2. Levenshtein distance-based fuzzy matching (fuzzy=True)
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+            pattern: Regex pattern or string to match
+            fuzzy: Whether to use fuzzy matching
+            threshold: Similarity threshold for fuzzy matching (0.0-1.0)
+
+        Returns:
+            True if the parameter value matches the pattern, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         if parameter_value is None:
             return False
@@ -297,7 +571,20 @@ class PropertyRules:
 
     @staticmethod
     def is_parameter_value_in_list(speckle_object: Base, parameter_name: str, value_list: list[Any] | str) -> bool:
-        """Checks if parameter value is in list."""
+        """Checks if parameter value is in list.
+
+        This implements the 'in list' predicate, supporting both:
+        1. Python lists
+        2. Comma-separated string lists
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+            value_list: List of values or comma-separated string
+
+        Returns:
+            True if parameter value is in the list, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
 
         if isinstance(value_list, str):
@@ -311,8 +598,20 @@ class PropertyRules:
         return is_value_in_list(parameter_value, value_list)
 
     @staticmethod
-    def _check_boolean_value(value: Any, values_to_match: tuple[str, ...]) -> bool:
-        """Check if a value matches any target value in expected format."""
+    def check_boolean_value(value: Any, values_to_match: tuple[str, ...]) -> bool:
+        """Check if a value matches any target value in expected format.
+
+        This is a helper for boolean parameter checking that handles:
+        - Boolean literals (True/False)
+        - String representations ("yes", "true", "1", etc.)
+
+        Args:
+            value: The value to check
+            values_to_match: Tuple of string values representing the target state
+
+        Returns:
+            True if value matches any target value, False otherwise
+        """
         if isinstance(value, bool):
             return value is (True if "true" in values_to_match else False)
 
@@ -323,35 +622,103 @@ class PropertyRules:
 
     @staticmethod
     def is_parameter_value_true(speckle_object: Base, parameter_name: str) -> bool:
-        """Check if parameter value represents true."""
+        """Check if parameter value represents true.
+
+        This implements the 'is true' predicate, handling various
+        representations of true values ("yes", "true", "1").
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+
+        Returns:
+            True if parameter value represents true, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-        return PropertyRules._check_boolean_value(parameter_value, ("yes", "true", "1"))
+        return PropertyRules.check_boolean_value(parameter_value, ("yes", "true", "1"))
 
     @staticmethod
     def is_parameter_value_false(speckle_object: Base, parameter_name: str) -> bool:
-        """Check if parameter value represents false."""
+        """Check if parameter value represents false.
+
+        This implements the 'is false' predicate, handling various
+        representations of false values ("no", "false", "0").
+
+        Args:
+            speckle_object: The Speckle object to check
+            parameter_name: The parameter name/path to check
+
+        Returns:
+            True if parameter value represents false, False otherwise
+        """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-        return PropertyRules._check_boolean_value(parameter_value, ("no", "false", "0"))
+        return PropertyRules.check_boolean_value(parameter_value, ("no", "false", "0"))
 
     @staticmethod
     def has_category(speckle_object: Base) -> bool:
-        """Check if object has category."""
+        """Check if object has category.
+
+        This is a convenience method specifically for checking
+        the existence of the 'category' property.
+
+        Args:
+            speckle_object: The Speckle object to check
+
+        Returns:
+            True if object has a category property, False otherwise
+        """
         return PropertyRules.has_parameter(speckle_object, "category")
 
     @staticmethod
     def is_category(speckle_object: Base, category_input: str) -> bool:
-        """Check if object matches category."""
+        """Check if object matches category.
+
+        This is a convenience method for filtering objects by category,
+        which is a common operation in Speckle.
+
+        Args:
+            speckle_object: The Speckle object to check
+            category_input: The category value to match
+
+        Returns:
+            True if object's category matches input, False otherwise
+        """
         category_value = PropertyRules.get_parameter_value(speckle_object, "category")
         return category_value == category_input
 
     @staticmethod
     def get_category_value(speckle_object: Base) -> str:
-        """Get object's category value."""
+        """Get object's category value.
+
+        This is a convenience method for retrieving an object's category.
+
+        Args:
+            speckle_object: The Speckle object to get category from
+
+        Returns:
+            The category value as a string
+        """
         return PropertyRules.get_parameter_value(speckle_object, "category")
 
     @staticmethod
-    def _try_boolean_comparison(value1: Any, value2: Any, allow_yes_no: bool) -> tuple[bool, bool]:
-        """Attempts to compare two values as booleans."""
+    def try_boolean_comparison(value1: Any, value2: Any, allow_yes_no: bool) -> tuple[bool, bool]:
+        """Attempts to compare two values as booleans.
+
+        This handles various boolean representations:
+        - Boolean literals (True/False)
+        - String representations ("true"/"false")
+        - Revit-style "Yes"/"No" strings (if allow_yes_no=True)
+
+        Args:
+            value1: First value to compare
+            value2: Second value to compare
+            allow_yes_no: Whether to convert Yes/No strings to booleans
+
+        Returns:
+            Tuple of (can_compare: bool, result: bool) where:
+            - can_compare indicates if both values could be interpreted as booleans
+            - result is the comparison result if can_compare is True
+        """
 
         def strict_convert_boolean(value: Any) -> Any:
             """Convert 'True'/'False' strings to booleans, and use `convert_revit_boolean` for Yes/No."""
@@ -380,7 +747,7 @@ class PropertyRules:
         return False, False
 
     @staticmethod
-    def _compare_values(
+    def compare_values(
         value1: Any,
         value2: Any,
         case_sensitive: bool = False,
@@ -390,26 +757,41 @@ class PropertyRules:
     ) -> bool:
         """Core logic for comparing two values with type handling and tolerance.
 
+        This is the comprehensive value comparison function that:
+        1. Tries boolean comparison first
+        2. Handles numeric string conversion
+        3. Implements case sensitivity options for strings
+        4. Uses tolerance-based floating point comparison
+        5. Falls back to regular equality
+
+        This function is used by multiple predicates.
+
         Args:
             value1: First value to compare
             value2: Second value to compare
             case_sensitive: Whether to perform case-sensitive string comparison
             tolerance: Tolerance for floating point comparisons
-            allow_yes_no_bools: Whether to convert Yes/No strings to booleans when comparing with boolean values
+            allow_yes_no_bools: Whether to convert Yes/No strings to booleans
             use_exact: Whether to use exact equality for numeric comparisons
+
         Returns:
-            bool: True if values are considered equal, False otherwise
+            True if values are considered equal, False otherwise
         """
         # Try boolean comparison first
-        can_compare, result = PropertyRules._try_boolean_comparison(value1, value2, allow_yes_no_bools)
+        can_compare, result = PropertyRules.try_boolean_comparison(value1, value2, allow_yes_no_bools)
         if can_compare:
             return result
 
         # Handle case where one value is a string that can be interpreted as a number
-        if isinstance(value1, str) and value1.replace(".", "", 1).isdigit():
-            value1 = float(value1)
-        if isinstance(value2, str) and value2.replace(".", "", 1).isdigit():
-            value2 = float(value2)
+        def safe_convert_to_number(val):
+            if isinstance(val, str):
+                val = val.strip()  # Remove whitespace
+                if val.replace(".", "", 1).replace("-", "", 1).isdigit():  # Handle negative numbers
+                    return float(val)
+            return val
+
+        value1 = safe_convert_to_number(value1)
+        value2 = safe_convert_to_number(value2)
 
         # For strings: Allow case insensitivity if specified
         if isinstance(value1, str) and isinstance(value2, str):
@@ -436,21 +818,26 @@ class PropertyRules:
     ) -> bool:
         """Compares a parameter value from a Speckle object with the provided value.
 
+        This implements the 'equal to' predicate with flexible comparison rules:
+        - Case insensitivity option for strings
+        - Tolerance-based comparison for floating point numbers
+        - Type conversion for common scenarios (numeric strings, Yes/No)
+
         Args:
-            speckle_object (Base): The Speckle object containing the parameter
-            parameter_name (str): Name of the parameter to compare
-            value_to_match: The value to compare against (float, string, int, etc.)
-            case_sensitive (bool): Whether to perform case-sensitive comparison for strings
-            tolerance (float): Tolerance for floating point comparisons
+            speckle_object: The Speckle object containing the parameter
+            parameter_name: Name of the parameter to compare
+            value_to_match: The value to compare against
+            case_sensitive: Whether to perform case-sensitive comparison for strings
+            tolerance: Tolerance for floating point comparisons
 
         Returns:
-            bool: True if values are considered equal, False otherwise
+            True if values are considered equal, False otherwise
         """
         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
         if parameter_value is None:
             return False
 
-        return PropertyRules._compare_values(
+        return PropertyRules.compare_values(
             parameter_value, value_to_match, case_sensitive, tolerance, allow_yes_no_bools=True
         )
 
@@ -478,7 +865,7 @@ class PropertyRules:
         if parameter_value is None:
             return True  # Non-existent parameters are considered not equal
 
-        return not PropertyRules._compare_values(
+        return not PropertyRules.compare_values(
             parameter_value, value_to_match, case_sensitive, tolerance, allow_yes_no_bools=True
         )
 
@@ -500,6 +887,6 @@ class PropertyRules:
         if parameter_value is None:
             return False
 
-        return PropertyRules._compare_values(
+        return PropertyRules.compare_values(
             parameter_value, value_to_match, case_sensitive=True, tolerance=0, allow_yes_no_bools=False, use_exact=True
         )

src/rules_old.py

@@ -1,756 +0,0 @@
-# import re
-# from typing import Any
-#
-# from Levenshtein import ratio
-# from specklepy.objects.base import Base
-#
-# from src.helpers import get_item, has_item, speckle_print
-# from src.inputs import PropertyMatchMode
-
-# We're going to define a set of rules that will allow us to filter and
-# process parameters in our Speckle objects. These rules will be encapsulated
-# in a class called `ParameterRules`.
-
-
-# class Rules:
-#     """A collection of rules for processing properties in Speckle objects.
-#
-#     Simple rules can be straightforwardly implemented as static methods that
-#     return boolean value to be used either as a filter or a condition.
-#     These can then be abstracted into returning lambda functions that  we can
-#     use in our main processing logic. By encapsulating these rules, we can easily
-#     extend or modify them in the future.
-#     """
-#
-#     @staticmethod
-#     def try_get_display_value(
-#         speckle_object: Base,
-#     ) -> list[Base] | None:
-#         """Try fetching the display value from a Speckle object.
-#
-#         This method encapsulates the logic for attempting to retrieve the display value from a
-#         Speckle object. It returns a list containing the display values if found,
-#         otherwise it returns None.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to extract the display value from.
-#
-#         Returns:
-#             Optional[List[Base]]: A list containing the display values.
-#                                   If no display value is found, returns None.
-#         """
-#         # Attempt to get the display value from the speckle_object
-#         raw_display_value = getattr(speckle_object, "displayValue", None) or getattr(
-#             speckle_object, "@displayValue", None
-#         )
-#
-#         # If no display value found, return None
-#         if raw_display_value is None:
-#             return None
-#
-#         # If display value found, filter out non-Base objects
-#         display_values = [value for value in raw_display_value if isinstance(value, Base)]
-#
-#         # If no valid display values found, return None
-#         if not display_values:
-#             return None
-#
-#         return display_values
-#
-#     @staticmethod
-#     def is_displayable_object(speckle_object: Base) -> bool:
-#         """Determines if a given Speckle object is displayable.
-#
-#         This method encapsulates the logic for determining if a Speckle object is displayable.
-#         It checks if the speckle_object has a display value and returns True if it does, otherwise it returns False.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#
-#         Returns:
-#             bool: True if the object has a display value, False otherwise.
-#         """
-#         # Check for direct displayable state using try_get_display_value
-#         display_values = Rules.try_get_display_value(speckle_object)
-#         if display_values and getattr(speckle_object, "id", None) is not None:
-#             return True
-#
-#         # Check for displayable state via definition, using try_get_display_value on the definition object
-#         definition = getattr(speckle_object, "definition", None)
-#         if definition:
-#             definition_display_values = Rules.try_get_display_value(definition)
-#             if definition_display_values and getattr(definition, "id", None) is not None:
-#                 return True
-#
-#         return False
-#
-#     @staticmethod
-#     def get_displayable_objects(flat_list_of_objects: list[Base]) -> list[Base]:
-#         """Filters a list of Speckle objects to only include displayable objects.
-#
-#         This function takes a list of Speckle objects and filters out the objects that are displayable.
-#         It returns a list containing only the displayable objects.
-#
-#         Args:
-#             flat_list_of_objects (List[Base]): The list of Speckle objects to filter.
-#         """
-#         return [
-#             speckle_object
-#             for speckle_object in flat_list_of_objects
-#             if Rules.is_displayable_object(speckle_object) and getattr(speckle_object, "id", None)
-#         ]
-#
-#
-# class PropertyRules:
-#     """A collection of rules for processing Revit parameters in Speckle objects."""
-#
-#     @staticmethod
-#     def has_parameter(speckle_object: Base, parameter_name: str, *_args, **_kwargs) -> bool:
-#         """Checks if the speckle_object has a parameter with the given name."""
-#         found, _ = ParameterSearch.lookup_parameter(speckle_object, parameter_name)
-#         return found
-#
-#     @staticmethod
-#     def get_parameter_value(
-#         speckle_object: Base,
-#         parameter_name: str,
-#         match_mode: PropertyMatchMode = PropertyMatchMode.MIXED,
-#         default_value: Any = None,
-#     ) -> Any:
-#         """Gets the value of a parameter if it exists."""
-#         found, value = ParameterSearch.lookup_parameter(speckle_object, parameter_name, match_mode)
-#         return value if found else default_value
-#
-#     @staticmethod
-#     def is_v3(speckle_object: Base) -> bool:
-#         """Determines if a Speckle object uses v3 parameter structure.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check
-#
-#         Returns:
-#             bool: True if object uses v3 structure, False otherwise
-#         """
-#         properties = get_item(speckle_object, "properties")
-#         return bool(properties and has_item(properties, "Parameters"))
-#
-#     # @staticmethod
-#     # def has_parameter(speckle_object: Base, parameter_name: str, *_args, **_kwargs) -> bool:
-#     #     """Checks if the speckle_object has a Revit parameter with the given name.
-#     #
-#     #     First checks direct properties, then determines if it's a v2 or v3 object structure
-#     #     and searches in the appropriate parameter hierarchy.
-#     #
-#     #     Args:
-#     #         speckle_object (Base): The Speckle object to check.
-#     #         parameter_name (str): The name of the parameter to check for.
-#     #         *_args: Extra positional arguments which are ignored.
-#     #         **_kwargs: Extra keyword arguments which are ignored.
-#     #
-#     #     Returns:
-#     #         bool: True if the object has the parameter, False otherwise.
-#     #     """
-#     #     # Check direct property first regardless of version
-#     #     if has_item(speckle_object, parameter_name):
-#     #         return True
-#     #
-#     #     if PropertyRules.is_v3(speckle_object):
-#     #         properties = get_item(speckle_object, "properties")
-#     #         parameters = get_item(properties, "Parameters")
-#     #         if parameters:
-#     #
-#     #             def search_v3_params(params: dict, search_name: str) -> bool:
-#     #                 for key, value in params.items():
-#     #                     if isinstance(value, dict):
-#     #                         # Check direct name match
-#     #                         if key.lower() == search_name.lower():
-#     #                             return True
-#     #                         # Check nested parameters
-#     #                         if search_v3_params(value, search_name):
-#     #                             return True
-#     #                 return False
-#     #
-#     #             return search_v3_params(parameters, parameter_name)
-#     #     else:
-#     #         # Handle v2 structure
-#     #         parameters = get_item(speckle_object, "parameters")
-#     #         if not parameters:
-#     #             return False
-#     #
-#     #         # Check direct parameter name match
-#     #         if has_item(parameters, parameter_name):
-#     #             return True
-#     #
-#     #         # Check nested parameters with name property
-#     #         def check_nested_name(value: Any) -> bool:
-#     #             if isinstance(value, dict):
-#     #                 return get_item(value, "name") == parameter_name
-#     #             return get_item(value, "name") == parameter_name if hasattr(value, "name") else False
-#     #
-#     #         return any(check_nested_name(param_value) for param_value in parameters.values() if param_value is not None)
-#     #
-#     #     return False
-#     #
-#     # @staticmethod
-#     # def get_parameter_value(
-#     #     speckle_object: Base,
-#     #     parameter_name: str,
-#     #     match_mode: PropertyMatchMode = PropertyMatchMode.MIXED,
-#     #     default_value: Any = None,
-#     # ) -> Any | None:
-#     #     """Retrieves the value of the specified parameter from the speckle_object.
-#     #
-#     #     First checks direct properties, then determines if it's a v2 or v3 object structure
-#     #     and retrieves from the appropriate parameter hierarchy.
-#     #
-#     #     Args:
-#     #             speckle_object (Base): The Speckle object to retrieve the parameter value from.
-#     #         parameter_name (str): The name of the parameter to retrieve the value for.
-#     #         match_mode (PropertyMatchMode): The matching mode to use for parameter lookup
-#     #         default_value: The default value to return if parameter not found.
-#     #
-#     #     Returns:
-#     #         The value of the parameter if found, else default_value.
-#     #     """
-#     #     # Check direct property first regardless of version
-#     #     if has_item(speckle_object, parameter_name):
-#     #         value = get_item(speckle_object, parameter_name)
-#     #         return value if value is not None else default_value
-#     #
-#     #     if PropertyRules.is_v3(speckle_object):
-#     #         return PropertyRules.get_v3_parameter(speckle_object, parameter_name, match_mode, default_value)
-#     #     else:
-#     #         return PropertyRules.get_v2_parameter(speckle_object, parameter_name, match_mode, default_value)
-#
-#     # @staticmethod
-#     # def get_v2_parameter(obj: Base, name: str, mode: PropertyMatchMode, default: Any) -> Any:
-#     #     """Get parameter value from v2 Speckle object structure.
-#     #
-#     #     Args:
-#     #         obj: Speckle object to get parameter from
-#     #         name: Parameter name to retrieve
-#     #         mode: Match mode for parameter lookup
-#     #         default: Default value if parameter not found
-#     #
-#     #     Returns:
-#     #         Parameter value if found, else default
-#     #     """
-#     #     parameters = get_item(obj, "parameters")
-#     #     if not parameters:
-#     #         return default
-#     #
-#     #     if mode == PropertyMatchMode.STRICT:
-#     #         return PropertyRules.strict_parameter_lookup(name, parameters, default)
-#     #
-#     #     def search_params(param_dict: dict, search_name: str, fuzzy: bool) -> Any:
-#     #         for key, value in param_dict.items():
-#     #             key_match = (key.lower() == search_name.lower()) or (fuzzy and search_name.lower() in key.lower())
-#     #             if key_match:
-#     #                 # Handle both direct values and nested parameter objects
-#     #                 return get_item(value, "value", value)
-#     #         return None
-#     #
-#     #     result = search_params(parameters, name, mode == PropertyMatchMode.FUZZY)
-#     #     return result if result is not None else default
-#     #
-#     # @staticmethod
-#     # def get_v3_parameter(obj: Base, name: str, mode: PropertyMatchMode, default: Any) -> Any:
-#     #     """Get parameter value from v3 Speckle object structure.
-#     #
-#     #     Args:
-#     #         obj: Speckle object to get parameter from
-#     #         name: Parameter name to retrieve
-#     #         mode: Match mode for parameter lookup
-#     #         default: Default value if parameter not found
-#     #
-#     #     Returns:
-#     #         Parameter value if found, else default
-#     #     """
-#     #     properties = get_item(obj, "properties")
-#     #     if not properties or not has_item(properties, "Parameters"):
-#     #         return default
-#     #
-#     #     parameters = get_item(properties, "Parameters")
-#     #     if not parameters:
-#     #         return default
-#     #
-#     #     if mode == PropertyMatchMode.STRICT:
-#     #         return PropertyRules.strict_parameter_lookup(name, parameters, default)
-#     #
-#     #     def search_nested(data: dict, search_name: str, fuzzy: bool) -> Any:
-#     #         for nested_key, value in data.items():
-#     #             if isinstance(value, dict):
-#     #                 key_match = (nested_key.lower() == search_name.lower()) or (
-#     #                     fuzzy and search_name.lower() in nested_key.lower()
-#     #                 )
-#     #
-#     #                 if key_match and has_item(value, "value"):
-#     #                     return get_item(value, "value")
-#     #
-#     #                 nested_result = search_nested(value, search_name, fuzzy)
-#     #                 if nested_result is not None:
-#     #                     return nested_result
-#     #         return None
-#     #
-#     #     result = search_nested(parameters, name, mode == PropertyMatchMode.FUZZY)
-#     #     return result if result is not None else default
-#     #
-#     # @staticmethod
-#     # def strict_parameter_lookup(name: str, parameters: dict, default: Any) -> Any:
-#     #     """Perform strict parameter lookup following exact path.
-#     #
-#     #     Args:
-#     #         name: Parameter path (dot separated)
-#     #         parameters: Parameters dictionary
-#     #         default: Default value if not found
-#     #
-#     #     Returns:
-#     #         Parameter value if found, else default
-#     #     """
-#     #     path_parts = name.split(".")
-#     #     current = parameters
-#     #
-#     #     for part in path_parts:
-#     #         if not current or not isinstance(current, dict):
-#     #             return default
-#     #
-#     #         # Find exact case-insensitive match
-#     #         key = next((k for k in current.keys() if k.lower() == part.lower()), None)
-#     #         if not key:
-#     #             return default
-#     #
-#     #         current = get_item(current, key)
-#     #
-#     #     # Handle both direct values and parameter objects
-#     #     if isinstance(current, dict):
-#     #         return get_item(current, "value", current)
-#     #     return current
-#
-#     @staticmethod
-#     def is_parameter_value(speckle_object: Base, parameter_name: str, value_to_match: Any) -> bool:
-#         """Checks if the value of the specified parameter matches the given value.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             value_to_match (Any): The value to match against.
-#
-#         Returns:
-#             bool: True if the parameter value matches the given value, False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         return parameter_value == value_to_match
-#
-#     @staticmethod
-#     def is_parameter_value_like(
-#         speckle_object: Base,
-#         parameter_name: str,
-#         pattern: str,
-#         fuzzy: bool = False,
-#         threshold: float = 0.8,
-#     ) -> bool:
-#         """Checks if the value of the specified parameter matches the given pattern.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             pattern (str): The pattern to match against.
-#             fuzzy (bool): If True, performs fuzzy matching using Levenshtein distance.
-#                           If False (default), performs exact pattern matching using regular expressions.
-#             threshold (float): The similarity threshold for fuzzy matching (default: 0.8).
-#                                Only applicable when fuzzy=True.
-#
-#         Returns:
-#             bool: True if the parameter value matches the pattern (exact or fuzzy), False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         if parameter_value is None:
-#             return False
-#
-#         if fuzzy:
-#             similarity = ratio(str(parameter_value), pattern)
-#             return similarity >= threshold
-#         else:
-#             return bool(re.match(pattern, str(parameter_value)))
-#
-#     @staticmethod
-#     def parse_number_from_string(input_string: str):
-#         """Attempts to parse an integer or float from a given string.
-#
-#         Args:
-#             input_string (str): The string containing the number to be parsed.
-#
-#         Returns:
-#             int or float: The parsed number, or raises ValueError if parsing is not possible.
-#         """
-#         try:
-#             # First try to convert it to an integer
-#             return int(input_string)
-#         except ValueError:
-#             # If it fails to convert to an integer, try to convert to a float
-#             try:
-#                 return float(input_string)
-#             except ValueError:
-#                 # Raise an error if neither conversion is possible
-#                 raise ValueError("Input string is not a valid integer or float")
-#
-#     @staticmethod
-#     def is_parameter_value_greater_than(speckle_object: Base, parameter_name: str, threshold: str) -> bool:
-#         """Checks if the value of the specified parameter is greater than the given threshold.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             threshold (Union[int, float]): The threshold value to compare against.
-#
-#         Returns:
-#             bool: True if the parameter value is greater than the threshold, False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         if parameter_value is None:
-#             return False
-#
-#         if not isinstance(parameter_value, int | float):
-#             raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
-#         return parameter_value > PropertyRules.parse_number_from_string(threshold)
-#
-#     @staticmethod
-#     def is_parameter_value_less_than(speckle_object: Base, parameter_name: str, threshold: str) -> bool:
-#         """Checks if the value of the specified parameter is less than the given threshold.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             threshold (Union[int, float]): The threshold value to compare against.
-#
-#         Returns:
-#             bool: True if the parameter value is less than the threshold, False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         if parameter_value is None:
-#             return False
-#         if not isinstance(parameter_value, int | float):
-#             raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
-#         return parameter_value < PropertyRules.parse_number_from_string(threshold)
-#
-#     @staticmethod
-#     def is_parameter_value_in_range(speckle_object: Base, parameter_name: str, value_range: str) -> bool:
-#         """Checks if the value of the specified parameter falls within the given range.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             value_range (str): The range to check against, in the format "min_value, max_value".
-#
-#         Returns:
-#             bool: True if the parameter value falls within the range (inclusive), False otherwise.
-#         """
-#         min_value, max_value = value_range.split(",")
-#         min_value = PropertyRules.parse_number_from_string(min_value)
-#         max_value = PropertyRules.parse_number_from_string(max_value)
-#
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         if parameter_value is None:
-#             return False
-#         if not isinstance(parameter_value, int | float):
-#             raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
-#
-#         return min_value <= parameter_value <= max_value
-#
-#     @staticmethod
-#     def is_parameter_value_in_range_expanded(
-#         speckle_object: Base,
-#         parameter_name: str,
-#         min_value: int | float,
-#         max_value: int | float,
-#         inclusive: bool = True,
-#     ) -> bool:
-#         """Checks if the value of the specified parameter falls within the given range.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             min_value (Union[int, float]): The minimum value of the range.
-#             max_value (Union[int, float]): The maximum value of the range.
-#             inclusive (bool): If True (default), the range is inclusive (min <= value <= max).
-#                               If False, the range is exclusive (min < value < max).
-#
-#         Returns:
-#             bool: True if the parameter value falls within the range (inclusive), False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         if parameter_value is None:
-#             return False
-#         if not isinstance(parameter_value, int | float):
-#             raise ValueError(f"Parameter value must be a number, got {type(parameter_value)}")
-#
-#         return min_value <= parameter_value <= max_value if inclusive else min_value < parameter_value < max_value
-#
-#     @staticmethod
-#     def is_parameter_value_in_list(speckle_object: Base, parameter_name: str, value_list: list[Any] | str) -> bool:
-#         """Checks if the value of the specified parameter is present in the given list of values.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             parameter_name (str): The name of the parameter to check.
-#             value_list (List[Any]): The list of values to check against.
-#
-#         Returns:
-#             bool: True if the parameter value is found in the list, False otherwise.
-#         """
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#
-#         if isinstance(value_list, str):
-#             value_list = [value.strip() for value in value_list.split(",")]
-#
-#         # parameter_value is effectively Any type, so to find its value in the value_list
-#         def is_value_in_list(value: Any, my_list: Any) -> bool:
-#             # Ensure that my_list is actually a list
-#             if isinstance(my_list, list):
-#                 return value in my_list or str(value) in my_list
-#             else:
-#                 speckle_print(f"Expected a list, got {type(my_list)} instead.")
-#                 return False
-#
-#         return is_value_in_list(parameter_value, value_list)
-#
-#     @staticmethod
-#     def _check_boolean_value(value: Any, values_to_match: tuple[str, ...]) -> bool:
-#         """Check if a value matches any target value in expected format."""
-#         if isinstance(value, bool):
-#             return value is (True if "true" in values_to_match else False)
-#
-#         if isinstance(value, str):
-#             return value.lower() in values_to_match
-#
-#         return False
-#
-#     @staticmethod
-#     def is_parameter_value_true(speckle_object: Base, parameter_name: str) -> bool:
-#         """Check if parameter value represents true (boolean True, 'yes', 'true', '1')."""
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         return PropertyRules._check_boolean_value(parameter_value, ("yes", "true", "1"))
-#
-#     @staticmethod
-#     def is_parameter_value_false(speckle_object: Base, parameter_name: str) -> bool:
-#         """Check if parameter value represents false (boolean False, 'no', 'false', '0')."""
-#         parameter_value = PropertyRules.get_parameter_value(speckle_object, parameter_name)
-#         return PropertyRules._check_boolean_value(parameter_value, ("no", "false", "0"))
-#
-#     @staticmethod
-#     def has_category(speckle_object: Base) -> bool:
-#         """Checks if the speckle_object has a 'category' parameter.
-#
-#         This method checks if the speckle_object has a 'category' parameter.
-#         If the 'category' parameter exists, it returns True; otherwise, it returns False.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#
-#         Returns:
-#             bool: True if the object has the 'category' parameter, False otherwise.
-#         """
-#         return PropertyRules.has_parameter(speckle_object, "category")
-#
-#     @staticmethod
-#     def is_category(speckle_object: Base, category_input: str) -> bool:
-#         """Checks if the value of the 'category' property matches the given input.
-#
-#         This method checks if the 'category' property of the speckle_object
-#         matches the given category_input. If they match, it returns True;
-#         otherwise, it returns False.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to check.
-#             category_input (str): The category value to compare against.
-#
-#         Returns:
-#             bool: True if the 'category' property matches the input, False otherwise.
-#         """
-#         category_value = PropertyRules.get_parameter_value(speckle_object, "category")
-#         return category_value == category_input
-#
-#     @staticmethod
-#     def get_category_value(speckle_object: Base) -> str:
-#         """Retrieves the value of the 'category' parameter from the speckle_object.
-#
-#         This method retrieves the value of the 'category' parameter from the speckle_object.
-#         If the 'category' parameter exists and its value is not None, it returns the value.
-#         If the 'category' parameter does not exist or its value is None, it returns an empty string.
-#
-#         Args:
-#             speckle_object (Base): The Speckle object to retrieve the 'category' parameter value from.
-#
-#         Returns:
-#             str: The value of the 'category' parameter if it exists and is not None, or an empty string otherwise.
-#         """
-#         return PropertyRules.get_parameter_value(speckle_object, "category")
-#
-#
-# class ParameterSearch:
-#     """Unified parameter search functionality for Speckle objects."""
-#
-#     @staticmethod
-#     def convert_revit_boolean(value: Any) -> Any:
-#         """Convert Revit-style Yes/No strings to boolean values.
-#
-#         Args:
-#             value: The value to potentially convert
-#
-#         Returns:
-#             bool if value is a Revit boolean string, original value otherwise
-#         """
-#         if isinstance(value, str):
-#             if value.lower() == "yes":
-#                 return True
-#             if value.lower() == "no":
-#                 return False
-#         return value
-#
-#     @staticmethod
-#     def search_parameters(
-#         params: dict, search_name: str, mode: PropertyMatchMode = PropertyMatchMode.STRICT
-#     ) -> tuple[bool, Any]:
-#         """Search for parameters using consistent matching logic.
-#
-#         Supports flexible property chain matching that can find paths like "Instance Parameters.Dimensions.Length"
-#         within longer chains like "properties.Parameters.Instance Parameters.Dimensions.Length.value".
-#         Uses STRICT matching by default for more predictable results.
-#
-#         Args:
-#             params: Parameter dictionary to search
-#             search_name: Name of parameter to find, can be dot-separated chain
-#             mode: Matching mode to use (STRICT by default, or FUZZY/MIXED for looser matching)
-#
-#         Returns:
-#             Tuple of (value_found: bool, value: Any)
-#         """
-#
-#         def matches_name(match_key: str, target: str, match_mode: PropertyMatchMode) -> bool:
-#             if match_mode == PropertyMatchMode.STRICT:
-#                 return match_key.lower() == target.lower()
-#             elif match_mode == PropertyMatchMode.FUZZY:
-#                 return target.lower() in match_key.lower()
-#             else:  # MIXED mode
-#                 return match_key.lower() == target.lower() or target.lower() in match_key.lower()
-#
-#         def try_get_value(obj: Any) -> Any:
-#             """Extract value from parameter object or return as is.
-#
-#             Handles both dict and Base objects, checking for 'value' property in both cases.
-#             Returns the 'value' if found, otherwise returns the original object.
-#             """
-#             # Handle dictionary objects
-#             if isinstance(obj, dict):
-#                 return obj.get("value", obj)
-#
-#             # Handle Base objects
-#             if isinstance(obj, Base):
-#                 return getattr(obj, "value", obj)
-#
-#             # For all other types, return as is
-#             return obj
-#
-#         # First try property chain lookup
-#         if "." in search_name:
-#             search_parts = search_name.split(".")
-#
-#             def try_match_path(current: dict, remaining_search_parts: list[str], depth: int = 0) -> tuple[bool, Any]:
-#                 if not isinstance(current, dict):
-#                     return False, None
-#
-#                 if not remaining_search_parts:  # We've matched all parts
-#                     return True, try_get_value(current)
-#
-#                 current_search = remaining_search_parts[0]
-#
-#                 # Try each key at current level
-#                 for key, item_value in current.items():
-#                     if matches_name(key, current_search, mode):
-#                         # Found a match for current part, recurse with rest
-#                         match_found, result = try_match_path(item_value, remaining_search_parts[1:], depth + 1)
-#                         if match_found:
-#                             return True, result
-#
-#                     # If no match found and value is a dict, try searching deeper
-#                     if isinstance(item_value, dict):
-#                         match_found, result = try_match_path(item_value, remaining_search_parts, depth)
-#                         if match_found:
-#                             return True, result
-#
-#                 return False, None
-#
-#             try:
-#                 found, value = try_match_path(params, search_parts)
-#                 if found:
-#                     return True, value
-#             except Exception:
-#                 pass  # Fall through to recursive search if chain lookup fails
-#
-#         # Recursive search through nested dictionaries
-#         def recursive_search(data: dict | Base, target: str) -> tuple[bool, Any]:
-#             if not isinstance(data, dict | Base):
-#                 return False, None
-#
-#             # Handle both dict and Base objects for iteration
-#             if isinstance(data, dict):
-#                 items = data.items()
-#             else:
-#                 items = [(k, getattr(data, k)) for k in dir(data) if not k.startswith("_")]
-#
-#             # First check current level
-#             for key, item_value in items:
-#                 if matches_name(key, target, mode):
-#                     return True, try_get_value(item_value)
-#
-#             # Then check nested levels
-#             for _, item_value in items:
-#                 if isinstance(item_value, dict | Base):
-#                     item_found, result = recursive_search(item_value, target)
-#                     if item_found:
-#                         return True, result
-#
-#             return False, None
-#
-#         return recursive_search(params, search_name.split(".")[-1] if "." in search_name else search_name)
-#
-#     @staticmethod
-#     def lookup_parameter(
-#         obj: Base, param_name: str, mode: PropertyMatchMode = PropertyMatchMode.MIXED
-#     ) -> tuple[bool, Any]:
-#         """Unified parameter lookup for both checking existence and getting values.
-#
-#         Args:
-#             obj: Speckle object to search
-#             param_name: Parameter name to find
-#             mode: Matching mode to use
-#
-#         Returns:
-#             Tuple of (found: bool, value: Any)
-#         """
-#         # Check direct property first
-#         if has_item(obj, param_name):
-#             value = get_item(obj, param_name)
-#             # Check if the direct property has a value field
-#             if isinstance(value, dict) and "value" in value:
-#                 return True, value["value"]
-#             return True, value
-#
-#         # Handle v3 structure
-#         if PropertyRules.is_v3(obj):
-#             properties = get_item(obj, "properties")
-#             if not properties or not has_item(properties, "Parameters"):
-#                 return False, None
-#
-#             parameters = get_item(properties, "Parameters")
-#             if not parameters:
-#                 return False, None
-#
-#             return ParameterSearch.search_parameters(parameters, param_name, mode)
-#
-#         # Handle v2 structure
-#         parameters = get_item(obj, "parameters")
-#         if not parameters:
-#             return False, None
-#
-#         return ParameterSearch.search_parameters(parameters, param_name, mode)

src/spreadsheet.py

@@ -1,38 +1,203 @@
+"""Module for reading and processing rules from a cloud hosted TSV file.
+
+This module handles the loading and processing of validation rules from external
+spreadsheet data, enabling non-technical users to define and modify rules.
+
+Key features:
+1. Reading from hosted TSV files (e.g., from Google Sheets)
+2. Processing rule numbers for consistent grouping
+3. Handling mixed data types in spreadsheet columns
+4. Validating rule structure and providing feedback
+5. Grouping related rule conditions for execution
+
+The spreadsheet format used follows a specific structure:
+- Rule Number: Groups related conditions together
+- Logic: WHERE/AND/CHECK to define condition relationships
+- Property Name: The property path to check
+- Predicate: The comparison operation (equals, greater than, etc.)
+- Value: The value to compare against
+- Message: The message to display for rule results
+- Severity: INFO/WARNING/ERROR level for failures
+"""
+
+import traceback
+
 import pandas as pd
 from pandas import DataFrame
+from pandas.core.groupby import DataFrameGroupBy
 
 
-def read_rules_from_spreadsheet(url: str) -> DataFrame | None:
-    """Reads a TSV file from a provided URL and returns a DataFrame.
+def process_rule_numbers(df: DataFrame) -> DataFrame:
+    """Process rule numbers in a DataFrame while preserving original rule identifiers.
+
+    This function handles various rule numbering scenarios:
+    1. Preserves existing rule numbers exactly as provided
+    2. Generates sequential numbers for missing rule numbers
+    3. Ensures all rows in a logical rule group have the same rule number
+
+    This is important because rule numbers determine how conditions are grouped
+    and executed together.
 
     Args:
-        url (str): The URL to the TSV file.
+        df: DataFrame with columns including 'Rule Number' and 'Logic'
 
     Returns:
-        DataFrame: Pandas DataFrame containing the TSV data.
+        DataFrame with processed rule numbers, where all related conditions
+        have the same rule number
     """
-    try:
-        # Since the output is a TSV, we use `pd.read_csv` with `sep='\t'` to specify tab-separated values.
-        df = pd.read_csv(url, sep="\t")
-        df = convert_mixed_columns(df)
+    # Create a copy to avoid modifying original
+    df = df.copy()
 
-        # Convert columns to appropriate types based on their content.
-        return df
+    # Initialize tracking variables
+    used_rule_nums = set()
+    processed_rule_nums = []
+    next_auto_num = 1  # For generating missing rule numbers only
 
-    except Exception as e:
-        print(f"Failed to read the TSV from the URL: {e}")
-        return None
+    # Find indices where Logic is 'WHERE' to identify rule group starts
+    where_indices = df[df["Logic"].str.upper() == "WHERE"].index
 
+    # Process each group
+    for i in range(len(where_indices)):
+        start_idx = where_indices[i]
+        end_idx = where_indices[i + 1] if i + 1 < len(where_indices) else len(df)
 
-def convert_mixed_columns(df):
-    """Converts columns in a DataFrame to appropriate types based on their content.
+        # Get slice of rows for this group
+        group_slice = df.iloc[start_idx:end_idx]
 
-    Args:
-        df (DataFrame): The DataFrame whose columns are to be converted.
+        # Try to get rule number from first row, fall back to "Rule #"
+        group_rule_num = (
+            group_slice["Rule Number"].iloc[0] if not pd.isna(group_slice["Rule Number"].iloc[0]) else "Rule #"
+        )
 
-    Returns:
-        DataFrame: The DataFrame with columns converted to appropriate types.
-    """
-    df = df.apply(lambda c: c.astype(object) if any(str(x).replace(".", "", 1).isdigit() for x in c) else c.astype(str))
+        if pd.isna(group_rule_num):
+            # If no rule number, generate next available number
+            while str(next_auto_num) in used_rule_nums:
+                next_auto_num += 1
+            group_rule_num = str(next_auto_num)
+            next_auto_num += 1
+        else:
+            # Keep the original rule number exactly as is
+            group_rule_num = str(group_rule_num)
+
+        # Update tracking
+        used_rule_nums.add(group_rule_num)
+
+        # Fill rule numbers for this group
+        processed_rule_nums.extend([group_rule_num] * len(group_slice))
+
+    # Update DataFrame with processed rule numbers
+    df["Rule Number"] = processed_rule_nums
+
+    return df
+
+
+def validate_rule_numbers(df: DataFrame) -> list[str]:
+    """Validate rule numbers and return any warnings or errors.
+
+    This checks for issues like:
+    1. Missing rule numbers
+    2. Non-integer rule numbers
+    3. Duplicate rule numbers
+
+    These validations help ensure rule integrity without being overly strict,
+    allowing for different user approaches to rule numbering.
+
+    Args:
+        df: DataFrame with processed rule numbers
+
+    Returns:
+        List of warning/error messages
+    """
+    messages = []
+
+    # Check for missing rule numbers
+    if df["Rule Number"].isna().any():
+        messages.append("Warning: Some rules are missing rule numbers")
+
+    # # Check for non-integer rule numbers
+    # non_int_mask = df["Rule Number"].apply(lambda x: not pd.isna(x) and not float(x).is_integer())
+    # if non_int_mask.any():
+    #     messages.append("Warning: Some rule numbers are not integers")
+
+    # Check for duplicate rule numbers in WHERE rows
+    where_rules = df[df["Logic"].str.upper() == "WHERE"]["Rule Number"]
+    duplicates = where_rules[where_rules.duplicated()]
+    if not duplicates.empty:
+        messages.append(f"Warning: Duplicate rule numbers found: {list(duplicates)}")
+
+    return messages
+
+
+def read_rules_from_spreadsheet(url: str) -> tuple[DataFrameGroupBy, list[str]] | tuple[None, list[str]]:
+    """Reads rules from a TSV file at the provided URL, processes them, and returns grouped rules.
+
+    This function is the main entry point for rule loading:
+    1. Reads the TSV file from the provided URL
+    2. Converts mixed type columns to appropriate types
+    3. Processes rule numbers for consistent grouping
+    4. Validates rule numbers and collects messages
+    5. Groups rules by rule number for execution
+
+    Args:
+        url: The URL to the TSV file containing rule definitions
+
+    Returns:
+        Tuple containing:
+        - DataFrameGroupBy object with rules grouped by rule number (or None if error)
+        - List of validation messages/warnings
+    """
+    try:
+        # Read the TSV file
+        # The TSV format is chosen for compatibility with Google Sheets
+        # and other spreadsheet applications
+        df = pd.read_csv(url, sep="\t")
+
+        # Convert mixed type columns
+        # This handles inconsistencies in spreadsheet data
+        df = convert_mixed_columns(df)
+
+        # Process rule numbers
+        # This ensures all related conditions have the same rule number
+        df = process_rule_numbers(df)
+
+        # Get validation messages
+        # These are warnings about potential issues with the rules
+        messages = validate_rule_numbers(df)
+
+        # Group by rule number
+        # This creates a DataFrameGroupBy object that groups related conditions
+        grouped_rules = df.groupby("Rule Number")
+
+        return grouped_rules, messages
+
+    except Exception as e:
+        # Handle any errors in reading or processing the spreadsheet
+        traceback.print_exc()
+        return None, [f"Failed to read the TSV from the URL: {str(e)}:{e.with_traceback(None)}"]
+
+
+def convert_mixed_columns(df: DataFrame) -> DataFrame:
+    """Converts columns in a DataFrame to appropriate types based on their content.
+
+    This handles common issues with spreadsheet data:
+    1. Numeric columns that contain strings
+    2. Mixed type columns
+    3. Empty cells and NaN values
+
+    The approach is to convert each column appropriately:
+    - Numeric columns remain as numbers
+    - Other columns are converted to strings, with empty strings for missing values
+
+    Args:
+        df: The DataFrame whose columns are to be converted
+
+    Returns:
+        DataFrame with columns converted to appropriate types
+    """
+    df = df.apply(
+        lambda c: c
+        if c.dropna().apply(lambda x: str(x).replace(".", "", 1).isdigit()).any()
+        else c.map(lambda x: "" if pd.isna(x) else str(x))
+    )
 
     return df

tests/conftest.py

@@ -2,67 +2,6 @@ import pytest
 from specklepy.objects.base import Base
 
 
-@pytest.fixture
-def v2_wall():
-    """Creates a v2-style Speckle wall object."""
-    wall = Base()
-    wall.id = "cdb18060dc48281909e94f0f1d8d3cc0"
-    wall.type = "W30(Fc24)"
-    wall.units = "mm"
-    wall.family = "Basic Wall"
-    wall.height = 1400
-    wall.flipped = False
-    wall.category = "Walls"
-    wall.elementId = "4479852"
-    wall.worksetId = "0"
-    wall.structural = True
-    wall.baseOffset = -2000
-    wall.topOffset = -600
-
-    # Create base line geometry
-    wall.baseLine = Base()
-    wall.baseLine.start = Base()
-    wall.baseLine.start.x = 22400.000000000007
-    wall.baseLine.start.y = 15199.999999999998
-    wall.baseLine.start.z = -2000.0000000000002
-    wall.baseLine.end = Base()
-    wall.baseLine.end.x = 22400.000000000015
-    wall.baseLine.end.y = 20500
-    wall.baseLine.end.z = -2000.0000000000002
-    wall.baseLine.units = "mm"
-    wall.baseLine.length = 5300.000000000002
-
-    # Create parameters structure
-    wall.parameters = Base()
-
-    # Standard parameter
-    wall.parameters["WALL_ATTR_WIDTH_PARAM"] = Base()
-    wall.parameters["WALL_ATTR_WIDTH_PARAM"].name = "Width"
-    wall.parameters["WALL_ATTR_WIDTH_PARAM"].value = 300
-    wall.parameters["WALL_ATTR_WIDTH_PARAM"].units = "mm"
-
-    # Parameter with GUID key
-    wall.parameters["ee1f33e1-5506-4a64-b87b-7b98d30aea52"] = Base()
-    wall.parameters["ee1f33e1-5506-4a64-b87b-7b98d30aea52"].name = "符号"
-    wall.parameters["ee1f33e1-5506-4a64-b87b-7b98d30aea52"].value = "W30"
-    wall.parameters["ee1f33e1-5506-4a64-b87b-7b98d30aea52"].isShared = True
-    wall.parameters[
-        "ee1f33e1-5506-4a64-b87b-7b98d30aea52"
-    ].internalDefinitionName = "ee1f33e1-5506-4a64-b87b-7b98d30aea52"
-
-    wall.parameters["STRUCTURAL_MATERIAL_PARAM"] = Base()
-    wall.parameters["STRUCTURAL_MATERIAL_PARAM"].name = "Structural Material"
-    wall.parameters["STRUCTURAL_MATERIAL_PARAM"].value = "Fc24"
-
-    # Create basic level reference
-    wall.level = Base()
-    wall.level.name = "1FL"
-    wall.level.elevation = 0
-    wall.level.units = "mm"
-
-    return wall
-
-
 @pytest.fixture
 def v3_wall():
     """Creates a v3-style Speckle wall object."""
@@ -79,25 +18,47 @@ def v3_wall():
 
     # Create location geometry
     wall.location = Base()
+    wall.location.id = "9c76b8de34382c9052965ee463f8374b"
     wall.location.start = Base()
     wall.location.start.x = 22400.000000000007
     wall.location.start.y = 15199.999999999998
     wall.location.start.z = 0
+    wall.location.start.id = "d0c4fdb2e11cc825e7f05f9dc88a0be1"
+    wall.location.start.units = "mm"
+    wall.location.start.speckle_type = "Objects.Geometry.Point"
     wall.location.end = Base()
     wall.location.end.x = 22400.000000000015
     wall.location.end.y = 20500
     wall.location.end.z = 0
+    wall.location.end.id = "3455575bfd8939f264d295b61e74156f"
+    wall.location.end.units = "mm"
+    wall.location.end.speckle_type = "Objects.Geometry.Point"
     wall.location.units = "mm"
+    wall.location.domain = Base()
+    wall.location.domain.id = "3b97feaad2dbcc2d894c9cec024a9bf2"
+    wall.location.domain.end = 17.388451443569522
+    wall.location.domain.start = -3.552713668866051e-14
+    wall.location.domain.speckle_type = "Objects.Primitive.Interval"
     wall.location.length = 5300.000000000002
+    wall.location.speckle_type = "Objects.Geometry.Line"
 
-    # Create nested properties structure
+    # Create level references
+    wall.level = Base()
+    wall.level.name = "1FL"
+    wall.level.units = "mm"
+    wall.level.elevation = 0
+
+    wall.topLevel = Base()
+    wall.topLevel.name = "1FL"
+    wall.topLevel.units = "mm"
+    wall.topLevel.elevation = 0
+
+    # Create properties structure
     wall.properties = Base()
     wall.properties.Parameters = Base()
-
-    # Type Parameters
     wall.properties.Parameters["Type Parameters"] = Base()
 
-    # Add Text section with GUID parameter
+    # Add Text section
     wall.properties.Parameters["Type Parameters"].Text = Base()
     wall.properties.Parameters["Type Parameters"].Text["符号"] = {
         "name": "符号",
@@ -105,6 +66,7 @@ def v3_wall():
         "internalDefinitionName": "ee1f33e1-5506-4a64-b87b-7b98d30aea52",
     }
 
+    # Add Structure section
     wall.properties.Parameters["Type Parameters"].Structure = Base()
     wall.properties.Parameters["Type Parameters"].Structure["Fc24 (0)"] = {
         "units": "mm",
@@ -113,20 +75,21 @@ def v3_wall():
         "thickness": 300,
     }
 
-    # Instance Parameters
+    # Add Construction section
+    wall.properties.Parameters["Type Parameters"].Construction = Base()
+    wall.properties.Parameters["Type Parameters"].Construction.Width = {
+        "name": "Width",
+        "units": "Millimeters",
+        "value": 300,
+        "internalDefinitionName": "WALL_ATTR_WIDTH_PARAM",
+    }
+
+    # Add Instance Parameters
     wall.properties.Parameters["Instance Parameters"] = Base()
     wall.properties.Parameters["Instance Parameters"].Structural = Base()
-    wall.properties.Parameters["Instance Parameters"].Structural.Structural = {"name": "Structural", "value": "Yes"}
-
-    # Create basic level references
-    wall.level = Base()
-    wall.level.name = "1FL"
-    wall.level.elevation = 0
-    wall.level.units = "mm"
-
-    wall.topLevel = Base()
-    wall.topLevel.name = "1FL"
-    wall.topLevel.elevation = 0
-    wall.topLevel.units = "mm"
+    wall.properties.Parameters["Instance Parameters"].Structural.Structural = {
+        "name": "Structural",
+        "value": "Yes",
+    }
 
     return wall

tests/test_comparisons.py

@@ -0,0 +1,86 @@
+from typing import Any
+
+import pytest
+
+from src.rules import PropertyRules
+
+
+class TestValueComparison:
+    """Test suite for value comparison functionality."""
+
+    @pytest.mark.parametrize(
+        "value1, value2",
+        [
+            # Basic numeric strings
+            ("1400", 1400.0),
+            ("1400.0", 1400),
+            ("1400.00", 1400),
+            # Whitespace handling
+            (" 1400 ", 1400.0),
+            ("  1400  ", 1400.0),
+            ("\t1400\n", 1400.0),
+            # Negative numbers
+            ("-1400", -1400.0),
+            (" -1400 ", -1400.0),
+            ("-1400.0", -1400),
+            # Zero handling
+            ("0", 0.0),
+            ("-0", 0.0),
+            ("0.0", 0),
+            # Simple integers
+            ("1", 1),
+            ("1.0", 1),
+        ],
+    )
+    def test_numeric_string_comparison(self, value1: Any, value2: Any):
+        """Test comparison of numeric strings with numbers."""
+        assert PropertyRules.compare_values(value1, value2)
+        # Test reverse comparison
+        assert PropertyRules.compare_values(value2, value1)
+
+    @pytest.mark.parametrize(
+        "value1, value2, expected",
+        [
+            ("Yes", True, True),
+            ("No", False, True),
+            ("yes", True, True),
+            ("no", False, True),
+            ("YES", True, True),
+            ("NO", False, True),
+            ("true", True, True),
+            ("false", False, True),
+            ("True", True, True),
+            ("False", False, True),
+        ],
+    )
+    def test_boolean_string_comparison(self, value1: str, value2: bool, expected: bool):
+        """Test comparison of boolean strings with booleans."""
+        assert PropertyRules.compare_values(value1, value2) == expected
+        # Test reverse comparison
+        assert PropertyRules.compare_values(value2, value1) == expected
+
+    @pytest.mark.parametrize(
+        "value1, value2, case_sensitive, expected",
+        [
+            ("hello", "HELLO", False, True),
+            ("hello", "HELLO", True, False),
+            ("Hello", "hello", False, True),
+            ("Hello", "Hello", True, True),
+        ],
+    )
+    def test_string_comparison(self, value1: str, value2: str, case_sensitive: bool, expected: bool):
+        """Test string comparison with case sensitivity options."""
+        assert PropertyRules.compare_values(value1, value2, case_sensitive=case_sensitive) == expected
+
+    @pytest.mark.parametrize(
+        "value1, value2, tolerance, expected",
+        [
+            (1.0001, 1.0, 1e-3, True),
+            (1.0001, 1.0, 1e-6, False),
+            (1.00000001, 1.0, 1e-6, True),
+            (-1.0001, -1.0, 1e-3, True),
+        ],
+    )
+    def test_float_comparison_tolerance(self, value1: float, value2: float, tolerance: float, expected: bool):
+        """Test float comparison with different tolerance levels."""
+        assert PropertyRules.compare_values(value1, value2, tolerance=tolerance) == expected

tests/test_function.py

@@ -10,32 +10,42 @@ from speckle_automate.fixtures import *  # noqa: F401, F403
 
 from src.function import automate_function
 from src.helpers import speckle_print
-from src.inputs import FunctionInputs
+from src.inputs import FunctionInputs, MinimumSeverity
 
 
-def test_function_run(test_automation_run_data: AutomationRunData, test_automation_token: str):
-    """Run an integration test for the automate function.
+class TestFunction:
+    """Test suite for the automate function."""
 
-    Args:
-        test_automation_run_data (AutomationRunData): The automation run data provided by sdk.
-        test_automation_token (str): The automation token.
+    def test_function_run(
+        self,
+        test_automation_run_data: AutomationRunData,
+        test_automation_token: str,
+    ):
+        """Run an integration test for the automate function.
 
-    """
-    speckle_print(str(test_automation_run_data))
-    speckle_print(str(test_automation_token))
+        Args:
+            test_automation_run_data (AutomationRunData): The automation run
+            data provided by sdk.
+            test_automation_token (str): The automation token.
 
-    """Run an integration test for the automate function."""
-    automation_context = AutomationContext.initialize(
-        test_automation_run_data, test_automation_token
-    )
-    default_url: str = (
-        "https://drive.google.com/uc?export=download&id=1hiPSw23eOaqd27QD_YsXvZg9PWm7_XBx"
-    )
+        """
+        speckle_print(str(test_automation_run_data))
+        speckle_print(str(test_automation_token))
 
-    automate_sdk = run_function(
-        automation_context,
-        automate_function,
-        FunctionInputs(spreadsheet_url=default_url),
-    )
+        """Run an integration test for the automate function."""
+        automation_context = AutomationContext.initialize(
+            test_automation_run_data, test_automation_token
+        )
+        default_url: str = "https://model-checker.speckle.systems/r/7YhnQyQNP_Ydv97QCwHbj7BWHrNkG022bez_jVkxbYs/tsv"
 
-    assert automate_sdk.run_status == AutomationStatus.SUCCEEDED
+        automate_sdk = run_function(
+            automation_context,
+            automate_function,
+            FunctionInputs(
+                spreadsheet_url=default_url,
+                minimum_severity=MinimumSeverity.INFO,
+                hide_skipped=True,
+            ),
+        )
+
+        assert automate_sdk.run_status == AutomationStatus.SUCCEEDED

tests/test_parameters.py

@@ -1,404 +1,524 @@
-import os
-from typing import Any
+"""Test suite for parameter handling functionality."""
 
 import pytest
-from dotenv import load_dotenv
-from speckle_automate import AutomationContext, AutomationRunData  # noqa: F401, F403
-
-# from speckle_automate.fixtures import *  # noqa: F401, F403
-from specklepy.api.client import SpeckleClient
-from specklepy.core.api import operations
 from specklepy.objects.base import Base
-from specklepy.transports.server import ServerTransport
 
-from helpers import speckle_print
 from src.rules import PropertyRules
 
 
-def load_test_objects(v2_wall: Any, v3_wall: Any) -> tuple[Base, Base]:
-    """Load test objects from a Speckle server."""
-    client = SpeckleClient(host="https://app.speckle.systems", use_ssl=True)
+class TestParameterHandling:
+    """Test suite for parameter handling functionality."""
 
-    load_dotenv(dotenv_path="../.env")
+    @pytest.fixture
+    def test_objects(self) -> Base:
+        """Pytest fixture to provide test objects."""
+        # Create a mock Base object with the required structure
+        v3_obj = Base()
+        v3_obj.properties = {
+            "Parameters": {
+                "category": "Walls",
+                "Width": 300,
+                "Construction": {"Width": 300},
+                "Instance Parameters": {
+                    "Dimensions": {"Length": 5300.000000000001},
+                    "Structural": {"Structural": {"value": "Yes"}},
+                    "Room Bounding": {"value": "Yes"},
+                    "top is attached": {"value": "No"},
+                },
+                "Type Parameters": {
+                    "Structure": {"Fc24 (0)": {"thickness": 300}},
+                    "Text": {"符号": {"value": "W30"}},
+                },
+                "Type": "W30(Fc24)",
+            }
+        }
+        v3_obj.speckle_type = "Revit"
+        return v3_obj
 
-    client.authenticate_with_token(os.getenv("SPECKLE_TOKEN"))
+    def test_deserialization_structure(self, test_objects):
+        """Test that objects are properly deserialized with correct structure."""
+        v3_obj = test_objects
 
-    transport = ServerTransport(client=client, stream_id=os.getenv("SPECKLE_PROJECT_ID"))
+        # Check base class type
+        assert isinstance(v3_obj, Base), f"Expected {v3_obj} to be an instance of Base"
 
-    speckle_print(v2_wall)
-    v2_obj = operations.receive("cdb18060dc48281909e94f0f1d8d3cc0", transport)
-    v3_obj = operations.receive("46f06fef727d64a0bbcbd7ced51e0cd2", transport)
+        # Check v3 structure
+        assert hasattr(v3_obj, "properties"), (
+            "v3_obj should have 'properties' attribute"
+        )
+        assert v3_obj.properties is not None, "v3_obj.properties should not be None"
+        assert "Parameters" in v3_obj.properties, (
+            "'Parameters' key should exist in v3_obj.properties"
+        )
 
-    # return v2_wall, v3_wall
-    return v2_obj, v3_obj
-
-
-@pytest.fixture
-def test_objects(v2_wall: Any, v3_wall: Any) -> tuple[Base, Base]:
-    """Pytest fixture to provide test objects."""
-    return load_test_objects(v2_wall, v3_wall)
-
-
-def test_deserialization_structure(test_objects):
-    """Test that objects are properly deserialized with correct structure."""
-    v2_obj, v3_obj = test_objects
-
-    # Check base class type
-    for obj in [v2_obj, v3_obj]:
-        assert isinstance(obj, Base), f"Expected {obj} to be an instance of Base"
-
-    # Check v2 structure
-    assert hasattr(v2_obj, "parameters"), "v2_obj should have 'parameters' attribute"
-    assert v2_obj["parameters"] is not None, "v2_obj['parameters'] should not be None"
-
-    # Check v3 structure
-    assert hasattr(v3_obj, "properties"), "v3_obj should have 'properties' attribute"
-    assert v3_obj["properties"] is not None, "v3_obj['properties'] should not be None"
-    assert "Parameters" in v3_obj["properties"], "'Parameters' key should exist in v3_obj['properties']"
-
-
-@pytest.mark.parametrize(
-    "param_name, expected_result",
-    [
-        ("category", True),  # Test parameters that should exist
-        ("WALL_ATTR_WIDTH_PARAM", True),  # Test nested parameters
-        ("WALL_ATTR_WIDTH_PARAM.value", True),
-        ("WALL_ATTR_WIDTH_PARAM.id", True),
-        ("WALL_ATTR_WIDTH_PARAM.units", True),
-        ("non_existent_param", False),  # Test non-existent parameters
-    ],
-)
-def test_v2_parameter_exists(test_objects, param_name, expected_result):
-    """Test parameter existence checking in v2 objects."""
-    v2_obj, _ = test_objects
-    assert PropertyRules.has_parameter(v2_obj, param_name) == expected_result
-
-
-@pytest.mark.parametrize(
-    "param_name",
-    [
-        "WALL_ATTR_WIDTH_PARAM.id",
-        "WALL_ATTR_WIDTH_PARAM.value",
-        "WALL_ATTR_WIDTH_PARAM",
-        "WALL_ATTR_WIDTH_PARAM.units",
-    ],
-)
-def test_v2_parameter_value_retrieval(test_objects, param_name):
-    """Test parameter value retrieval in v2 objects."""
-    v2_obj, _ = test_objects
-    assert PropertyRules.get_parameter_value(v2_obj, param_name)
-
-
-@pytest.mark.parametrize(
-    "param_name, expected_result",
-    [
-        ("category", True),  # Test parameters that should exist
-        ("Width", True),  # Test nested parameters
-        ("non_existent_param", False),  # Test non-existent parameters
-    ],
-)
-def test_v3_parameter_exists(test_objects, param_name, expected_result):
-    """Test parameter existence checking in v3 objects."""
-    _, v3_obj = test_objects
-    assert PropertyRules.has_parameter(v3_obj, param_name) == expected_result
-
-
-@pytest.mark.parametrize(
-    "param_name_1, param_name_2",
-    [
-        (
-            "properties.Parameters.Instance Parameters.Dimensions.Length.value",
-            "Instance Parameters.Dimensions.Length",
-        ),
-    ],
-)
-def test_v3_parameter_search_equivalence(test_objects, param_name_1, param_name_2):
-    """Test parameter existence checking equivalence in v3 objects."""
-    _, v3_obj = test_objects
-    assert PropertyRules.get_parameter_value(v3_obj, param_name_1) == PropertyRules.get_parameter_value(
-        v3_obj, param_name_2
+    @pytest.mark.parametrize(
+        "param_name, expected_result",
+        [
+            ("category", True),  # Test parameters that should exist
+            ("Width", True),  # Test nested parameters
+            ("non_existent_param", False),  # Test non-existent parameters
+        ],
     )
+    def test_v3_parameter_exists(self, test_objects, param_name, expected_result):
+        """Test parameter existence checking in v3 objects."""
+        v3_obj = test_objects
+        assert PropertyRules.has_parameter(v3_obj, param_name) == expected_result
 
+    @pytest.mark.parametrize(
+        "param_name_1, param_name_2",
+        [
+            # Test direct value access
+            (
+                "location.length",
+                "location.length",
+            ),
+            # Test .value key access
+            (
+                "Type Parameters.Text.符号",
+                "Type Parameters.Text.符号.value",
+            ),
+        ],
+    )
+    def test_v3_parameter_search_equivalence(
+        self,
+        v3_wall,
+        param_name_1,
+        param_name_2,
+    ):
+        """Test parameter existence checking equivalence in v3 objects."""
+        assert PropertyRules.get_parameter_value(
+            v3_wall, param_name_1
+        ) == PropertyRules.get_parameter_value(v3_wall, param_name_2)
 
-@pytest.mark.parametrize(
-    "obj_version, param_name, expected_value, default_value",
-    [
-        # Test direct parameters
-        ("v2", "category", "Walls", None),
-        ("v3", "category", "Walls", None),
-        # Test nested parameters - using both internal and friendly names
-        ("v2", "WALL_ATTR_WIDTH_PARAM", 300, None),
-        ("v3", "Construction.Width", 300, None),
-        # Test parameters with units
-        ("v2", "CURVE_ELEM_LENGTH", 5300.000000000001, None),
-        ("v3", "Instance Parameters.Dimensions.Length", 5300.000000000001, None),
-        # Test non-existent parameters with a default value
-        ("v2", "parameters.non_existent", "default", "default"),
-        ("v3", "properties.Parameters.non_existent", "default", "default"),
-    ],
-)
-def test_parameter_value_retrieval(test_objects, obj_version, param_name, expected_value, default_value):
-    """Test parameter value retrieval from both v2 and v3 objects."""
-    v2_obj, v3_obj = test_objects
-    obj = v2_obj if obj_version == "v2" else v3_obj
-    result = PropertyRules.get_parameter_value(obj, param_name, default_value=default_value)
-    assert result == expected_value
+    @pytest.mark.parametrize(
+        "param_name, expected_value, default_value",
+        [
+            # Test direct parameters
+            ("category", "Walls", None),
+            # Test nested parameters - using both internal and friendly names
+            ("Construction.Width", 300, None),
+            # Test parameters with units
+            (
+                "Instance Parameters.Dimensions.Length",
+                5300.000000000001,
+                None,
+            ),
+            # Test non-existent parameters with a default value
+            (
+                "properties.Parameters.non_existent",
+                "default",
+                "default",
+            ),
+        ],
+    )
+    def test_parameter_value_retrieval(
+        self,
+        test_objects,
+        param_name,
+        expected_value,
+        default_value,
+    ):
+        """Test parameter value retrieval from v3 objects."""
+        v3_obj = test_objects
+        result = PropertyRules.get_parameter_value(
+            v3_obj,
+            param_name,
+            default_value=default_value,
+        )
+        assert result == expected_value
 
+    @pytest.mark.parametrize(
+        "param_name, expected_value, expected_result",
+        [
+            ("category", "Walls", True),  # Test exact match
+            ("Width", 300, True),  # Test numeric match
+            ("category", "Windows", False),  # Test non-match
+        ],
+    )
+    def test_v3_parameter_value_matching(
+        self,
+        test_objects,
+        param_name,
+        expected_value,
+        expected_result,
+    ):
+        """Test parameter value matching in v3 objects."""
+        v3_obj = test_objects
+        assert (
+            PropertyRules.is_parameter_value(
+                v3_obj,
+                param_name,
+                expected_value,
+            )
+            == expected_result
+        )
 
-@pytest.mark.parametrize(
-    "param_name, expected_value, expected_result",
-    [
-        ("category", "Walls", True),  # Test exact match
-        ("WALL_ATTR_WIDTH_PARAM", 300, True),  # Test numeric match
-        ("category", "Windows", False),  # Test non-match
-    ],
-)
-def test_v2_parameter_value_matching(test_objects, param_name, expected_value, expected_result):
-    """Test parameter value matching in v2 objects."""
-    v2_obj, _ = test_objects
-    assert PropertyRules.is_parameter_value(v2_obj, param_name, expected_value) == expected_result
+    @pytest.mark.parametrize(
+        "comparison_func, param_name, value, expected_result",
+        [
+            (
+                PropertyRules.is_parameter_value_greater_than,
+                "Width",
+                "200",
+                True,
+            ),  # Test greater than
+            (
+                PropertyRules.is_parameter_value_less_than,
+                "Width",
+                "400",
+                True,
+            ),  # Test less than
+            (
+                PropertyRules.is_parameter_value_in_range,
+                "Width",
+                "200,400",
+                True,
+            ),  # Test in range
+        ],
+    )
+    def test_v3_parameter_numeric_comparisons(
+        self, test_objects, comparison_func, param_name, value, expected_result
+    ):
+        """Test numeric parameter comparisons in v3 objects."""
+        v3_obj = test_objects
+        assert comparison_func(v3_obj, param_name, value) == expected_result
 
+    @pytest.mark.parametrize(
+        "param_name, pattern, fuzzy, expected_result",
+        [
+            ("category", "^Walls$", False, True),  # Test exact pattern matches
+            ("category", "Walls", True, True),  # Test fuzzy matches
+            ("category", "Wall", False, True),  # Test partial pattern matches
+            ("category", "^Windows$", False, False),  # Test non-matches
+        ],
+    )
+    def test_v3_parameter_value_like(
+        self, test_objects, param_name, pattern, fuzzy, expected_result
+    ):
+        """Test pattern matching on parameter values in v3 objects."""
+        v3_obj = test_objects
+        assert (
+            PropertyRules.is_parameter_value_like(
+                v3_obj, param_name, pattern, fuzzy=fuzzy
+            )
+            == expected_result
+        )
 
-@pytest.mark.parametrize(
-    "param_name, expected_value, expected_result",
-    [
-        ("category", "Walls", True),  # Test exact match
-        ("Width", 300, True),  # Test numeric match
-        ("category", "Windows", False),  # Test non-match
-    ],
-)
-def test_v3_parameter_value_matching(test_objects, param_name, expected_value, expected_result):
-    """Test parameter value matching in v3 objects."""
-    _, v3_obj = test_objects
-    assert PropertyRules.is_parameter_value(v3_obj, param_name, expected_value) == expected_result
+    @pytest.mark.parametrize(
+        "param_name, valid_list, expected_result",
+        [
+            (
+                "category",
+                ["Walls", "Windows", "Doors"],
+                True,
+            ),  # Test value in list
+            (
+                "category",
+                "Walls,Windows,Doors",
+                True,
+            ),  # Test comma-separated string list
+            (
+                "category",
+                ["Windows", "Doors"],
+                False,
+            ),  # Test value not in list
+        ],
+    )
+    def test_v3_parameter_lists(
+        self,
+        test_objects,
+        param_name,
+        valid_list,
+        expected_result,
+    ):
+        """Test list-based parameter checks in v3 objects."""
+        v3_obj = test_objects
+        assert (
+            PropertyRules.is_parameter_value_in_list(
+                v3_obj,
+                param_name,
+                valid_list,
+            )
+            == expected_result
+        )
 
+    @pytest.mark.parametrize(
+        "param_name, expected_result",
+        [
+            ("Room Bounding", True),  # Test true values
+            ("top is attached", False),  # Test false values
+            ("Top is Attached", False),  # Case sensitivity test
+        ],
+    )
+    def test_v3_boolean_parameters(
+        self,
+        test_objects,
+        param_name,
+        expected_result,
+    ):
+        """Test boolean parameter checks in v3 objects."""
+        v3_obj = test_objects
+        if expected_result:
+            assert PropertyRules.is_parameter_value_true(v3_obj, param_name)
+        else:
+            assert PropertyRules.is_parameter_value_false(v3_obj, param_name)
 
-@pytest.mark.parametrize(
-    "comparison_func, param_name, value, expected_result",
-    [
-        (PropertyRules.is_parameter_value_greater_than, "WALL_ATTR_WIDTH_PARAM", "200", True),  # Test greater than
-        (PropertyRules.is_parameter_value_less_than, "WALL_ATTR_WIDTH_PARAM", "400", True),  # Test less than
-        (PropertyRules.is_parameter_value_in_range, "WALL_ATTR_WIDTH_PARAM", "200,400", True),  # Test in range
-    ],
-)
-def test_v2_parameter_numeric_comparisons(test_objects, comparison_func, param_name, value, expected_result):
-    """Test numeric parameter comparisons in v2 objects."""
-    v2_obj, _ = test_objects
-    assert comparison_func(v2_obj, param_name, value) == expected_result
+    @pytest.mark.parametrize(
+        "attribute, value, expected",
+        [
+            # Test numeric value comparisons
+            (
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                300,
+                True,
+            ),
+            (
+                "Instance Parameters.Dimensions.Length",
+                5300.000000000002,
+                True,
+            ),
+            (
+                "Instance Parameters.Dimensions.Length",
+                5300,
+                True,
+            ),
+            # Test string value comparisons
+            (
+                "Type Parameters.Text.符号.value",
+                "W30",
+                True,
+            ),
+            (
+                "Instance Parameters.Structural.Structural.value",
+                "Yes",
+                True,
+            ),
+            # Test non-matches
+            (
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                301,
+                False,
+            ),
+            (
+                "nonexistent_param",
+                "any_value",
+                False,
+            ),
+        ],
+    )
+    def test_v3_parameter_value_comparisons(
+        self,
+        test_objects,
+        attribute,
+        value,
+        expected,
+    ):
+        """Test value comparisons using v3 wall parameters."""
+        assert PropertyRules.is_equal_value(test_objects, attribute, value) == expected
 
+    @pytest.mark.parametrize(
+        "wall, attribute, value, expected",
+        [
+            # V3 wall tests
+            (
+                "v3_wall",
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                300,
+                True,
+            ),
+            ("v3_wall", "type", "W30(Fc24)", True),
+            (
+                "v3_wall",
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                300.0001,
+                False,
+            ),
+            (
+                "v3_wall",
+                "location.length",
+                5300.000000000002,
+                False,
+            ),
+            (
+                "v3_wall",
+                "location.length",
+                5300,
+                False,
+            ),
+        ],
+    )
+    def test_identical_comparisons(
+        self,
+        test_objects,
+        wall,
+        attribute,
+        value,
+        expected,
+    ):
+        """Test identical value comparisons on v3 wall."""
+        if attribute == "type":
+            # Use case-insensitive comparison for type parameter
+            assert (
+                PropertyRules.is_equal_value(
+                    test_objects,
+                    attribute,
+                    value,
+                )
+                == expected
+            )
+        else:
+            # Use strict comparison for other parameters
+            assert (
+                PropertyRules.is_identical_value(
+                    test_objects,
+                    attribute,
+                    value,
+                )
+                == expected
+            )
 
-@pytest.mark.parametrize(
-    "comparison_func, param_name, value, expected_result",
-    [
-        (PropertyRules.is_parameter_value_greater_than, "Width", "200", True),  # Test greater than
-        (PropertyRules.is_parameter_value_less_than, "Width", "400", True),  # Test less than
-        (PropertyRules.is_parameter_value_in_range, "Width", "200,400", True),  # Test in range
-    ],
-)
-def test_v3_parameter_numeric_comparisons(test_objects, comparison_func, param_name, value, expected_result):
-    """Test numeric parameter comparisons in v3 objects."""
-    _, v3_obj = test_objects
-    assert comparison_func(v3_obj, param_name, value) == expected_result
+    @pytest.mark.parametrize(
+        "wall, attribute, value",
+        [
+            # V3 wall tests
+            (
+                "v3_wall",
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                301,
+            ),
+            (
+                "v3_wall",
+                "Type Parameters.Text.符号.value",
+                "W31",
+            ),
+            (
+                "v3_wall",
+                "nonexistent_param",
+                "any_value",
+            ),
+        ],
+    )
+    def test_not_equal_comparisons(
+        self,
+        test_objects,
+        wall,
+        attribute,
+        value,
+    ):
+        """Test not equal comparisons on v3 wall."""
+        assert PropertyRules.is_not_equal_value(test_objects, attribute, value)
 
+    @pytest.mark.parametrize(
+        "attribute, value, expected_equal, expected_identical",
+        [
+            # Test Yes/No conversion in equals (should convert)
+            (
+                "Instance Parameters.Structural.Structural.value",
+                True,
+                True,
+                False,
+            ),  # Yes vs True
+            (
+                "Instance Parameters.Structural.Structural.value",
+                "Yes",
+                True,
+                True,
+            ),  # Yes vs "Yes"
+            (
+                "Instance Parameters.Structural.Structural.value",
+                "yes",
+                True,
+                False,
+            ),  # Yes vs "yes"
+        ],
+    )
+    def test_boolean_conversions(
+        self,
+        test_objects,
+        attribute,
+        value,
+        expected_equal,
+        expected_identical,
+    ):
+        """Test conversion of Yes/No strings to boolean values."""
+        assert (
+            PropertyRules.is_equal_value(test_objects, attribute, value)
+            == expected_equal
+        )
+        assert (
+            PropertyRules.is_identical_value(test_objects, attribute, value)
+            == expected_identical
+        )
 
-@pytest.mark.parametrize(
-    "param_name, pattern, fuzzy, expected_result",
-    [
-        ("category", "^Walls$", False, True),  # Test exact pattern matches
-        ("category", "Walls", True, True),  # Test fuzzy matches
-        ("category", "Wall", False, True),  # Test partial pattern matches
-        ("category", "^Windows$", False, False),  # Test non-matches
-    ],
-)
-def test_v2_parameter_value_like(test_objects, param_name, pattern, fuzzy, expected_result):
-    """Test pattern matching on parameter values in v2 objects."""
-    v2_obj, _ = test_objects
-    assert PropertyRules.is_parameter_value_like(v2_obj, param_name, pattern, fuzzy=fuzzy) == expected_result
+    @pytest.mark.parametrize(
+        "wall, attribute, expected_value",
+        [
+            # V3 wall tests
+            (
+                "v3_wall",
+                "Type Parameters.Structure.Fc24 (0).thickness",
+                "300",
+            ),
+            (
+                "v3_wall",
+                "Instance Parameters.Dimensions.Length",
+                "5300.000000000002",
+            ),
+        ],
+    )
+    def test_numeric_string_handling(
+        self,
+        test_objects,
+        wall,
+        attribute,
+        expected_value,
+    ):
+        """Test handling of numeric strings in v3 wall."""
+        assert PropertyRules.is_equal_value(
+            test_objects,
+            attribute,
+            expected_value,
+        )
 
-
-@pytest.mark.parametrize(
-    "param_name, pattern, fuzzy, expected_result",
-    [
-        ("category", "^Walls$", False, True),  # Test exact pattern matches
-        ("category", "Walls", True, True),  # Test fuzzy matches
-        ("category", "Wall", False, True),  # Test partial pattern matches
-        ("category", "^Windows$", False, False),  # Test non-matches
-    ],
-)
-def test_v3_parameter_value_like(test_objects, param_name, pattern, fuzzy, expected_result):
-    """Test pattern matching on parameter values in v3 objects."""
-    _, v3_obj = test_objects
-    assert PropertyRules.is_parameter_value_like(v3_obj, param_name, pattern, fuzzy=fuzzy) == expected_result
-
-
-@pytest.mark.parametrize(
-    "param_name, valid_list, expected_result",
-    [
-        ("category", ["Walls", "Windows", "Doors"], True),  # Test value in list
-        ("category", "Walls,Windows,Doors", True),  # Test comma-separated string list
-        ("category", ["Windows", "Doors"], False),  # Test value not in list
-    ],
-)
-def test_v2_parameter_lists(test_objects, param_name, valid_list, expected_result):
-    """Test list-based parameter checks in v2 objects."""
-    v2_obj, _ = test_objects
-    assert PropertyRules.is_parameter_value_in_list(v2_obj, param_name, valid_list) == expected_result
-
-
-@pytest.mark.parametrize(
-    "param_name, valid_list, expected_result",
-    [
-        ("category", ["Walls", "Windows", "Doors"], True),  # Test value in list
-        ("category", "Walls,Windows,Doors", True),  # Test comma-separated string list
-        ("category", ["Windows", "Doors"], False),  # Test value not in list
-    ],
-)
-def test_v3_parameter_lists(test_objects, param_name, valid_list, expected_result):
-    """Test list-based parameter checks in v3 objects."""
-    _, v3_obj = test_objects
-    assert PropertyRules.is_parameter_value_in_list(v3_obj, param_name, valid_list) == expected_result
-
-
-@pytest.mark.parametrize(
-    "param_name, expected_result",
-    [
-        ("WALL_ATTR_ROOM_BOUNDING.value", True),  # Test true values
-        ("wall_top_is_attached", False),  # Test false values
-    ],
-)
-def test_v2_boolean_parameters(test_objects, param_name, expected_result):
-    """Test boolean parameter checks in v2 objects."""
-    v2_obj, _ = test_objects
-    if expected_result:
-        assert PropertyRules.is_parameter_value_true(v2_obj, param_name)
-    else:
-        assert PropertyRules.is_parameter_value_false(v2_obj, param_name)
-
-
-@pytest.mark.parametrize(
-    "param_name, expected_result",
-    [
-        ("Room Bounding", True),  # Test true values
-        ("top is attached", False),  # Test false values
-        ("Top is Attached", False),  # Case sensitivity test
-    ],
-)
-def test_v3_boolean_parameters(test_objects, param_name, expected_result):
-    """Test boolean parameter checks in v3 objects."""
-    _, v3_obj = test_objects
-    if expected_result:
-        assert PropertyRules.is_parameter_value_true(v3_obj, param_name)
-    else:
-        assert PropertyRules.is_parameter_value_false(v3_obj, param_name)
-
-
-@pytest.mark.parametrize(
-    "param_name, expected_value, expected_result",
-    [
-        # Test numeric value comparisons
-        ("WALL_ATTR_WIDTH_PARAM", 300, True),
-        ("WALL_ATTR_WIDTH_PARAM.value", 300, True),
-        ("baseLine.length", 5300.000000000002, True),
-        # Test string value comparisons
-        ("STRUCTURAL_MATERIAL_PARAM.value", "Fc24", True),
-        ("ee1f33e1-5506-4a64-b87b-7b98d30aea52.value", "W30", True),
-        # Test non-matches
-        ("WALL_ATTR_WIDTH_PARAM", 301, False),
-        ("nonexistent_param", "any_value", False),
-    ],
-)
-def test_v2_parameter_value_comparisons(v2_wall, param_name, expected_value, expected_result):
-    """Test value comparisons using v2 wall parameters."""
-    assert PropertyRules.is_equal_value(v2_wall, param_name, expected_value) == expected_result
-
-
-@pytest.mark.parametrize(
-    "attribute, value, expected",
-    [
-        # Test numeric value comparisons
-        ("Type Parameters.Structure.Fc24 (0).thickness", 300, True),
-        ("location.length", 5300.000000000002, True),
-        ("location.length", 5300, True),
-        # Test string value comparisons
-        ("Type Parameters.Text.符号.value", "W30", True),
-        ("Instance Parameters.Structural.Structural.value", "Yes", True),
-        # Test non-matches
-        ("Type Parameters.Structure.Fc24 (0).thickness", 301, False),
-        ("nonexistent_param", "any_value", False),
-    ],
-)
-def test_v3_parameter_value_comparisons(v3_wall, attribute, value, expected):
-    """Test value comparisons using v3 wall parameters."""
-    assert PropertyRules.is_equal_value(v3_wall, attribute, value) == expected
-
-
-@pytest.mark.parametrize(
-    "wall, attribute, value, expected",
-    [
-        # V2 wall tests
-        ("v2_wall", "WALL_ATTR_WIDTH_PARAM.value", 300, True),
-        ("v2_wall", "type", "W30(Fc24)", True),
-        ("v2_wall", "WALL_ATTR_WIDTH_PARAM.value", 300.0001, False),
-        # V3 wall tests
-        ("v3_wall", "Type Parameters.Structure.Fc24 (0).thickness", 300, True),
-        ("v3_wall", "type", "W30(Fc24)", True),
-        ("v3_wall", "Type Parameters.Structure.Fc24 (0).thickness", 300.0001, False),
-        ("v3_wall", "location.length", 5300.000000000002, True),
-        ("v3_wall", "location.length", 5300, False),
-    ],
-)
-def test_identical_comparisons(request, wall, attribute, value, expected):
-    """Test identical value comparisons on both wall versions."""
-    wall_instance = request.getfixturevalue(wall)
-    assert PropertyRules.is_identical_value(wall_instance, attribute, value) == expected
-
-
-@pytest.mark.parametrize(
-    "wall, attribute, value",
-    [
-        # V2 wall tests
-        ("v2_wall", "WALL_ATTR_WIDTH_PARAM.value", 301),
-        ("v2_wall", "STRUCTURAL_MATERIAL_PARAM.value", "Fc25"),
-        ("v2_wall", "nonexistent_param", "any_value"),
-        # V3 wall tests
-        ("v3_wall", "Type Parameters.Structure.Fc24 (0).thickness", 301),
-        ("v3_wall", "Type Parameters.Text.符号.value", "W31"),
-        ("v3_wall", "nonexistent_param", "any_value"),
-    ],
-)
-def test_not_equal_comparisons(request, wall, attribute, value):
-    """Test not equal comparisons on both wall versions."""
-    wall_instance = request.getfixturevalue(wall)
-    assert PropertyRules.is_not_equal_value(wall_instance, attribute, value)
-
-
-@pytest.mark.parametrize(
-    "attribute, value, expected_equal, expected_identical",
-    [
-        # Test Yes/No conversion in equals (should convert)
-        ("Instance Parameters.Structural.Structural.value", True, True, False),  # Yes vs True
-        ("Instance Parameters.Structural.Structural.value", "Yes", True, True),  # Yes vs "Yes"
-        ("Instance Parameters.Structural.Structural.value", "yes", True, False),  # Yes vs "yes"
-    ],
-)
-def test_boolean_conversions(v3_wall, attribute, value, expected_equal, expected_identical):
-    """Test conversion of Yes/No strings to boolean values."""
-    assert PropertyRules.is_equal_value(v3_wall, attribute, value) == expected_equal
-    assert PropertyRules.is_identical_value(v3_wall, attribute, value) == expected_identical
-
-
-@pytest.mark.parametrize(
-    "wall, attribute, expected_value",
-    [
-        # V2 wall tests
-        ("v2_wall", "WALL_ATTR_WIDTH_PARAM.value", "300"),
-        ("v2_wall", "baseLine.length", "5300.000000000002"),
-        # V3 wall tests
-        ("v3_wall", "Type Parameters.Structure.Fc24 (0).thickness", "300"),
-        ("v3_wall", "location.length", "5300.000000000002"),
-    ],
-)
-def test_numeric_string_handling(wall, attribute, expected_value, request):
-    """Test handling of numeric strings in both wall versions."""
-    wall_instance = request.getfixturevalue(wall)  # Retrieve fixture dynamically
-    assert PropertyRules.is_equal_value(wall_instance, attribute, expected_value)
+    @pytest.mark.parametrize(
+        "param_name, substring, expected_result",
+        [
+            (
+                "speckle_type",
+                "Revit",
+                True,
+            ),  # Should pass as it does not contain Revit
+            (
+                "speckle_type",
+                "NotPresent",
+                True,
+            ),  # Should pass as it doesn't contain
+            (
+                "speckle_type",
+                "",
+                False,
+            ),  # Should fail as empty string is contained in any string
+            (
+                "non_existent",
+                "anything",
+                True,
+            ),  # Should pass as non-existent can't contain
+        ],
+    )
+    def test_parameter_value_not_contains(
+        self,
+        test_objects,
+        param_name,
+        substring,
+        expected_result,
+    ):
+        """Test negative substring matching on parameter values."""
+        v3_obj = test_objects
+        assert (
+            PropertyRules.is_parameter_value_not_containing(
+                v3_obj,
+                param_name,
+                substring,
+            )
+            == expected_result
+        )

tests/test_rule_processing.py

@@ -0,0 +1,36 @@
+"""Tests for rule processing functionality."""
+
+import pandas as pd
+import pytest
+
+
+@pytest.fixture
+def explicit_check_rule():
+    """Create a rule using explicit CHECK format."""
+    return pd.DataFrame(
+        {
+            "Rule Number": [1, 1, 1],
+            "Logic": ["WHERE", "AND", "CHECK"],
+            "Property Name": ["category", "width", "material"],
+            "Predicate": ["matches", "greater than", "matches"],
+            "Value": ["Walls", "200", "Concrete"],
+            "Message": ["Test message", "", ""],
+            "Severity": ["Error", "", ""],
+        }
+    )
+
+
+@pytest.fixture
+def legacy_rule():
+    """Create a rule using legacy format (last AND is implicit check)."""
+    return pd.DataFrame(
+        {
+            "Rule Number": [1, 1, 1],
+            "Logic": ["WHERE", "AND", "AND"],
+            "Property Name": ["category", "width", "material"],
+            "Predicate": ["matches", "greater than", "matches"],
+            "Value": ["Walls", "200", "Concrete"],
+            "Message": ["Test message", "", ""],
+            "Severity": ["Error", "", ""],
+        }
+    )

tests/test_user_entry.py

@@ -16,8 +16,8 @@ from src.rule_processor import SeverityLevel, get_severity
         ("ERROR", SeverityLevel.ERROR),
         ("error", SeverityLevel.ERROR),
         ("Error", SeverityLevel.ERROR),
-        ("WARN", SeverityLevel.WARNING),  # Invalid → Defaults to ERROR
-        ("warn", SeverityLevel.WARNING),  # Invalid → Defaults to ERROR
+        ("WARN", SeverityLevel.WARNING),  
+        ("warn", SeverityLevel.WARNING),  
         ("Critical", SeverityLevel.ERROR),  # Invalid → Defaults to ERROR
         ("Severe", SeverityLevel.ERROR),  # Invalid → Defaults to ERROR
         ("", SeverityLevel.ERROR),  # Empty string → Defaults to ERROR

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