Walker Steps
Walker steps are the building blocks for graph traversals. Each step performs a specific operation on the traversal, such as moving the position, filtering elements, or collecting results.
What are Walker Steps?
Walker steps are chainable operations that build a graph traversal. Each step performs a specific operation on the traversal, such as:
- Moving the traversal position (vertices, edges, head, tail)
- Filtering elements (filter)
- Limiting results (limit, first)
- Collecting results (collect)
- Modifying the graph (mutate)
- And many more
Available Steps
Traversal Initiation
- vertices - Start traversal from vertices matching criteria
- vertices_by_id - Start traversal from vertices with specific IDs
Traversal Movement
- detour - Create a sub-traversal from the current position
- edges - Traverse along edges
- head - Move to source vertices of edges
- tail - Move to target vertices of edges
Filtering and Limiting
- filter - Filter elements based on a predicate
- first - Get only the first element
- take - Take a specified number of elements
Context and Data Handling
- push_context - Associate custom data with traversal elements
- default_context - Use predefined context for common patterns
- mutate_context - Modify context during traversal
Terminal Operations
- collect - Gather results into a collection
- count - Count elements in the traversal
- into_iter - Convert traversal to an iterator
- fold - Fold elements into an accumulated value
- map - Transform elements during traversal
- reduce - Combine elements using a reduction function
Control Flow
- control_flow - Control traversal flow and early termination
Side effects
Type Management
- boxed - Reduce type complexity and improve compile times
Debugging
- dbg - Print debug information during traversal