# Groggy Release Notes Draft

## 🚀 Major Features Completed

### ✅ Python API Complete (All 6 Phases)
- **Full Python bindings** with `import groggy as gr`
- **String-based query parsing**: `g.filter_nodes("salary > 120000")`
- **Flexible node/edge creation**: Support for kwargs, dicts, tuples
- **String ID resolution**: `g.add_edge("alice", "bob", uid_key="id")`
- **Bulk operations**: `g.add_nodes(node_data)`, `g.add_edges(edge_data)`
- **Node mapping**: `g.get_node_mapping(uid_key="id")` for string-to-ID lookup

### ✅ Subgraph Architecture Refactor
- **Proper graph references**: PySubgraph now uses core `Rc<RefCell<Graph>>` architecture
- **Batch operations**: `subgraph.set(department="Engineering")` works correctly
- **Column access**: `subgraph['salary']` returns attribute columns
- **Full Graph API**: Subgraphs behave identically to Graphs

### ✅ Algorithm Return Types
- **All algorithms return Subgraph objects** (not PyResultHandle)
- **In-place operations**: `connected_components(inplace=True, attr_name="component_id")`
- **Chainable operations**: `g.filter_nodes('age < 30').filter_nodes('role == "engineer"')`

### ✅ Query Engine Enhancements
- **Enhanced string parsing**: Supports logical operators (AND, OR, NOT)
- **Multiple filter formats**: NodeFilter objects, string queries, attribute filters
- **Optimized parsing**: Direct conversion from strings to Rust filters

### ✅ Version Control System
- **Git-like functionality**: commits, branches, checkout, merge
- **Historical views**: Query graph state at any commit
- **Performance optimized**: Sub-millisecond commit times
- **Comprehensive statistics**: Memory usage, commit history tracking

### ✅ Memory Optimization
- **Advanced attribute compression**: CompactText, SmallInt variants
- **Pool-based node/edge management**: Efficient ID reuse
- **Memory statistics**: Real-time memory usage tracking
- **1000+ node graph support**: Validated performance at scale

### ✅ Development Quality
- **Clean builds**: All compiler warnings eliminated
- **Comprehensive test suite**: Stress testing and performance validation
- **Error handling**: Proper Python exceptions and error messages

## 🔧 Technical Implementation Details

### Core Architecture
- **Rust backend**: High-performance graph operations in Rust core
- **PyO3 bindings**: Seamless Python-Rust interoperability
- **Reference counting**: `Rc<RefCell<>>` for safe subgraph operations
- **Memory safety**: Zero-copy operations where possible

### Performance Characteristics
- **Sub-millisecond operations**: Filtering, traversal, attribute access
- **Linear scaling**: Efficient algorithms for large graphs
- **Memory efficient**: Compressed attribute storage

### API Design Philosophy
- **Pythonic**: Familiar syntax following Python conventions
- **Chainable**: Fluent API for complex operations
- **Flexible**: Multiple ways to achieve the same result
- **Consistent**: Same interface across Graph and Subgraph

## 📊 Validation & Testing
- **Comprehensive benchmarks**: Performance comparisons with NetworkX
- **Memory stress tests**: Large graph validation
- **API compatibility**: Ensures consistent behavior across operations
- **Edge case handling**: Robust error handling and recovery