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Exercises/exercise_3/README.md

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+# Exercise 3: Externalized Configuration 📊
+
+This exercise demonstrates how to move validation rules from code to external configuration, making the system more maintainable and user-friendly.
+
+## What's New ✨
+1. External rule configuration via spreadsheet
+2. Enhanced rule processing system
+3. More flexible validation framework
+4. Improved reporting and feedback
+
+## Key Changes from Exercise 2 📈
+
+### Input Schema Changes
+```python
+class FunctionInputs(AutomateBase):
+    spreadsheet_url: str = Field(
+        title="Spreadsheet URL",
+        description="URL of the spreadsheet containing validation rules"
+    )
+```
+
+### Rule Processing System
+```python
+def apply_rules_to_objects(
+    speckle_objects: List[Base],
+    rules_df: pd.DataFrame,
+    automate_context: AutomationContext,
+) -> dict[str, Tuple[List[Base], List[Base]]]:
+    # Rule application logic
+    ...
+```
+
+## System Architecture 🏗️
+
+### Spreadsheet Structure
+| Rule Number | Property Name | Predicate | Value | Message | Report Severity |
+|------------|---------------|-----------|--------|---------|-----------------|
+| 1          | Height        | greater than | 2.5    | Height check | Warning        |
+| 2          | Material      | exists    | -      | Material required | Error         |
+
+### Rule Processing Flow
+1. Load rules from spreadsheet
+2. Parse and validate rule definitions
+3. Apply rules to objects
+4. Generate comprehensive results
+5. Report outcomes with appropriate severity
+
+## Key Learning Points 📝
+- [ ] Separating configuration from code
+- [ ] Building flexible rule processors
+- [ ] Working with external data sources
+- [ ] Creating maintainable automation systems
+- [ ] Implementing complex validation logic
+- [ ] Enhanced error handling and reporting
+
+## Testing 🧪
+Run the test file:
+```bash
+pytest tests/local_test_exercise3.py::test_function_run
+```