Implementation Guide for Graph Backends

This guide will walk you through the process of implementing a new graph backend for the Graph API. While the Graph API provides several ready-to-use implementations (like SimpleGraph and PetGraph), you might want to build your own implementation to support specific requirements or optimize for particular use cases.

Overview

Implementing a graph backend involves satisfying the requirements of the Graph trait and its associated types. This guide will walk you through:

1. Understanding the core components needed for a graph implementation
2. Creating the fundamental data structures
3. Implementing the required traits
4. Building support for indexing (optional but recommended)
5. Testing your implementation

Core Components

A Graph API implementation requires several components:

1. Graph Structure: The primary data structure that stores vertices and edges
2. Vertex and Edge IDs: Unique identifiers for graph elements
3. References: Structures that refer to vertices and edges
4. Iterators: Types for traversing vertices and edges
5. Index Support: Optional components for efficient element lookup by property values

Step 1: Define IDs and Basic Structures

Start by defining your graph ID types and core data structure:

#![allow(unused)]
fn main() {
// Example vertex and edge IDs
pub struct MyVertexId {
    label: u16,    // Identifies the variant of the vertex enum
    index: u32,    // Unique index within that label
}

pub struct MyEdgeId {
    label: u16,    // Identifies the variant of the edge enum
    index: u32,    // Unique index within that label
    from: MyVertexId,
    to: MyVertexId,
}

// Import the necessary traits
use graph_api_lib::{
    Graph, Element, EdgeSearch, VertexSearch,
    SupportsVertexLabelIndex, SupportsEdgeLabelIndex, SupportsVertexHashIndex,
    SupportsVertexRangeIndex, SupportsEdgeRangeIndex, SupportsVertexFullTextIndex,
    SupportsEdgeAdjacentLabelIndex, SupportsClear, SupportsElementRemoval
};

// Main graph structure
pub struct MyGraph<Vertex, Edge>
where
    Vertex: Element,  // From graph_api_lib
    Edge: Element,    // From graph_api_lib
{
    // Your internal storage goes here
    // Example:
    vertices: Vec<YourVertexStorage<Vertex>>,
    edges: Vec<YourEdgeStorage<Edge>>,
    // More fields as needed (indexes, etc.)
}
}

Step 2: Define Reference Types

Create reference types that will be returned when accessing vertices and edges:

#![allow(unused)]
fn main() {
pub struct MyVertexReference<'graph, Graph>
where
    Graph: graph_api_lib::Graph,
{
    id: Graph::VertexId,
    weight: &'graph Graph::Vertex,
    // Additional fields if needed
}

pub struct MyVertexReferenceMut<'graph, Graph>
where
    Graph: graph_api_lib::Graph,
{
    id: Graph::VertexId,
    weight: &'graph mut Graph::Vertex,
    // Additional fields (like a reference to indexes)
    indexes: &'graph mut YourIndexStorage,
}

// Similar for EdgeReference and EdgeReferenceMut
}

Step 3: Implement the Required Traits

Now implement the required traits for your reference types:

#![allow(unused)]
fn main() {
impl<'graph, Graph> graph_api_lib::VertexReference<'graph, Graph> for MyVertexReference<'graph, Graph>
where
    Graph: graph_api_lib::Graph,
{
    fn id(&self) -> Graph::VertexId {
        self.id
    }

    fn weight(&self) -> &Graph::Vertex {
        self.weight
    }

    fn project<
        'reference,
        T: graph_api_lib::Project<'reference, <Graph as graph_api_lib::Graph>::Vertex>,
    >(
        &'reference self,
    ) -> Option<T> {
        graph_api_lib::Project::project(self.weight)
    }
}

// Implement VertexReferenceMut, EdgeReference, EdgeReferenceMut similarly
}

Step 4: Define Iterator Types

Create iterator types for walking through vertices and edges:

#![allow(unused)]
fn main() {
pub struct MyVertexIter<'search, 'graph, Graph>
where
    Graph: graph_api_lib::Graph + 'graph,
{
    // Internal state needed for iteration
    // Example:
    vertices: &'graph [YourVertexStorage<Graph::Vertex>],
    current_label: usize,
    current_index: usize,
    count: usize,
    limit: usize,
}

// Implement Iterator for MyVertexIter

impl<'graph, Graph> Iterator for MyVertexIter<'_, 'graph, Graph>
where
    Graph: graph_api_lib::Graph<VertexId=MyVertexId> + 'graph,
{
    type Item = MyVertexReference<'graph, Graph>;

    fn next(&mut self) -> Option<Self::Item> {
        // Your iterator implementation
        // Return the next vertex reference, or None if done
    }
}

// Similarly for MyEdgeIter
}

Step 5: Implement the Graph Trait

Now implement the Graph trait for your graph structure:

#![allow(unused)]
fn main() {
// First implement the core Graph trait
impl<Vertex, Edge> Graph for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    // Define the core types
    type Vertex = Vertex;
    type Edge = Edge;
    type VertexId = MyVertexId;
    type EdgeId = MyEdgeId;

    // Reference types
    type VertexReference<'graph> = MyVertexReference<'graph, Self>
    where
        Self: 'graph;
    type VertexReferenceMut<'graph> = MyVertexReferenceMut<'graph, Self>
    where
        Self: 'graph;
    type EdgeReference<'graph> = MyEdgeReference<'graph, Self>
    where
        Self: 'graph;
    type EdgeReferenceMut<'graph> = MyEdgeReferenceMut<'graph, Self>
    where
        Self: 'graph;

    // Iterator types
    type EdgeIter<'search, 'graph> = MyEdgeIter<'search, 'graph, Self>
    where
        Self: 'graph;
    type VertexIter<'search, 'graph> = MyVertexIter<'search, 'graph, Self>
    where
        Self: 'graph;

    // Implement the core graph operations
    fn add_vertex(&mut self, vertex: Self::Vertex) -> Self::VertexId {
        // Implementation details
    }

    fn add_edge(
        &mut self,
        from: Self::VertexId,
        to: Self::VertexId,
        edge: Self::Edge,
    ) -> Self::EdgeId {
        // Implementation details
    }


    fn vertex(&self, id: Self::VertexId) -> Option<Self::VertexReference<'_>> {
        // Implementation details
    }

    fn vertex_mut(&mut self, id: Self::VertexId) -> Option<Self::VertexReferenceMut<'_>> {
        // Implementation details
    }

    fn vertices<'search>(
        &self,
        vertex_search: &VertexSearch<'search, Self>,
    ) -> Self::VertexIter<'search, '_> {
        // Implementation details
    }

    fn edge(&self, id: Self::EdgeId) -> Option<Self::EdgeReference<'_>> {
        // Implementation details
    }

    fn edge_mut(&mut self, id: Self::EdgeId) -> Option<Self::EdgeReferenceMut<'_>> {
        // Implementation details
    }

    fn edges<'search>(
        &self,
        id: Self::VertexId,
        search: &EdgeSearch<'search, Self>,
    ) -> Self::EdgeIter<'search, '_> {
        // Implementation details
    }

    // No clear method here - it's moved to the SupportsClear trait
}

// Then implement support traits for the features you want to provide
// Implement SupportsElementRemoval if you want to support removing vertices and edges
impl<Vertex, Edge> SupportsElementRemoval for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    fn remove_vertex(&mut self, id: Self::VertexId) -> Option<Self::Vertex> {
        // Implementation details for removing a vertex
        // Remember to handle connected edges and update indexes
    }

    fn remove_edge(&mut self, id: Self::EdgeId) -> Option<Self::Edge> {
        // Implementation details for removing an edge
        // Remember to update adjacency lists and indexes
    }
}

impl<Vertex, Edge> SupportsVertexLabelIndex for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    // Any trait-specific methods would go here
}

impl<Vertex, Edge> SupportsEdgeLabelIndex for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    // Any trait-specific methods would go here
}

impl<Vertex, Edge> SupportsVertexHashIndex for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    // Any trait-specific methods would go here
}

// Add more support trait implementations as needed

// Implement SupportsClear if you want to support clearing the graph
impl<Vertex, Edge> SupportsClear for MyGraph<Vertex, Edge>
where
    Vertex: Element,
    Edge: Element,
{
    fn clear(&mut self) {
        // Clear all graph data
    }
}
}

Step 6: Implement Indexing (Optional)

If your graph supports indexes, you'll need to implement the index handling. This typically involves:

1. Creating a mutation listener for updating indexes on vertex/edge changes
2. Creating storage for different index types (hash, range, full-text)
3. Implementing index update logic when vertices or edges are modified

#![allow(unused)]
fn main() {
// Example MutationListener for vertex modifications
pub struct MyVertexMutationListener<'reference, Element> {
    // References to indexes and ID information
    indexes: &'reference mut YourIndexStorage,
    id: YourInternalId,
}

impl<'reference, Element> graph_api_lib::MutationListener<'reference, Element>
for MyVertexMutationListener<'reference, Element>
where
    Element: graph_api_lib::Element,
{
    fn update(&mut self, index: <Element::Label as Label>::Index, before: Value, after: Value) {
        // Update the indexes with the changed value
        // Remove old index entry
        // Add new index entry
    }
}
}

Step 7: Advanced Features

Consider implementing additional features:

1. Custom Traversal Optimizations: For specific types of queries
2. Specialized Index Types: For domain-specific data types
3. Persistence Layer: If your graph needs to be saved/loaded
4. Concurrency Support: For multi-threaded access

Step 8: Testing

Test your implementation using the Graph API's test suite:

#![allow(unused)]
fn main() {
#[cfg(test)]
mod test {
    use crate::MyGraph;
    use graph_api_test::test_suite;

    test_suite!(MyGraph::new());
}
}

Best Practices

1. Optimized ID Types: Use small, efficient ID types (consider using newtype patterns)
2. Memory Efficiency: Consider spatial locality and data structure layout
3. Index Handling: Carefully manage indexes to avoid inconsistencies
4. Error Handling: Provide meaningful errors for invalid operations
5. Documentation: Document the specific characteristics of your implementation

Example: Implementing a Simple Adjacency List Graph

Here's a sketch of how you might implement a simple adjacency list graph:

#![allow(unused)]
fn main() {
pub struct AdjListGraph<V, E> {
    vertices: Vec<Option<V>>,
    edges: Vec<Option<EdgeData<E>>>,
    adjacency: Vec<Vec<EdgeIndex>>, // Outgoing edges for each vertex
}

struct EdgeData<E> {
    edge: E,
    from: VertexIndex,
    to: VertexIndex,
}

// Implement the necessary traits...
}

Next Steps

Implementing a graph backend requires careful attention to detail, but the Graph API's trait system provides a clear structure to follow. By implementing the core traits and considering performance implications, you can create a specialized graph backend that perfectly fits your use case.

Remember to check the source code of existing implementations like SimpleGraph for more detailed examples of how to handle complex scenarios like indexing and traversal.