# Enhanced add_edges FFI Implementation Summary

## Overview

Successfully implemented enhanced parameter support for the `add_edges` method in the Groggy FFI, providing flexible node ID mapping and custom field name support.

## New Parameters Implemented

### 1. `uid_key` Parameter
- **Purpose**: Map custom column names to node identifiers
- **Usage**: `g.add_edges(edges, uid_key='custom_id_field')`
- **Supports**: String-based node IDs that get resolved to internal node indices
- **Format Support**: Works with tuples, dictionaries, and tuple-with-attributes

### 2. `source` and `target` Parameters
- **Purpose**: Specify custom field names for edge endpoints in dictionary format
- **Usage**: `g.add_edges(edges, uid_key='entity_id', source='from_obj', target='to_obj')`
- **Use Case**: API discovery scenarios where field names vary (e.g., `source='object_type', target='return_type'`)

## Implementation Details

### Files Modified
- `/Users/michaelroth/Documents/Code/groggy/python-groggy/src/ffi/api/graph.rs`
  - Enhanced `add_edges` method signature
  - Added support for custom field name resolution
  - Implemented proper error handling with descriptive messages

### Method Signature
```rust
#[pyo3(signature = (edges, uid_key=None, node_mapping=None, source=None, target=None))]
pub fn add_edges(
    &mut self,
    py: Python,
    edges: &PyAny,
    uid_key: Option<&str>,
    node_mapping: Option<HashMap<String, usize>>,
    source: Option<&str>,
    target: Option<&str>,
) -> PyResult<Vec<usize>>
```

### Error Handling
- Graceful handling of missing source/target fields with descriptive KeyError messages
- Proper resolution of string node IDs with meaningful error messages for missing nodes
- Type validation for different edge formats

## Usage Examples

### Basic uid_key Usage
```python
# Add nodes with custom ID field
nodes = [
    {'user_id': 'alice', 'name': 'Alice'},
    {'user_id': 'bob', 'name': 'Bob'}
]
g.add_nodes(nodes, uid_key='user_id')

# Add edges using string IDs
edges = [('alice', 'bob')]
g.add_edges(edges, uid_key='user_id')
```

### Custom Source/Target Fields
```python
# API discovery use case
api_objects = [
    {'object_type': 'User', 'description': 'User entity'},
    {'object_type': 'Post', 'description': 'Post entity'}
]
g.add_nodes(api_objects, uid_key='object_type')

method_data = [
    {'object_type': 'User', 'return_type': 'Post', 'method': 'getPosts'}
]
g.add_edges(method_data, uid_key='object_type', 
           source='object_type', target='return_type')
```

### Mixed Approaches
```python
# Different source/target field names in same graph
dependencies = [
    {'from_service': 'auth', 'to_service': 'user', 'type': 'auth'},
    {'caller': 'order', 'callee': 'user', 'type': 'data'}
]

g.add_edges([dependencies[0]], uid_key='service_name',
           source='from_service', target='to_service')
g.add_edges([dependencies[1]], uid_key='service_name', 
           source='caller', target='callee')
```

## Backward Compatibility

All existing functionality remains unchanged:
- Traditional `node_mapping` parameter still works
- Tuple format `(source, target)` and `(source, target, attrs)` unchanged
- Dictionary format with default 'source'/'target' fields unchanged

## Testing

Created comprehensive test suites:
- `test_uid_key_add_edges.py`: uid_key parameter validation
- `test_source_target_params.py`: source/target parameter testing
- `test_comprehensive_add_edges.py`: All parameter combinations
- `example_uid_key_usage.py`: Usage documentation

## Benefits

1. **Flexible Data Integration**: Handle various data formats without preprocessing
2. **API Discovery Support**: Map method relationships with custom field names
3. **Backward Compatible**: Existing code continues to work unchanged
4. **Error Resilient**: Proper error handling with descriptive messages
5. **Consistent Pattern**: Matches existing `add_nodes` uid_key pattern

## Build Status

- ✅ Successfully compiled with maturin
- ✅ All tests passing
- ✅ Error handling validated
- ✅ Comprehensive parameter combinations tested
