swarms/examples/multi_agent/graphworkflow_examples/rustworkx_examples

Rustworkx Backend Examples

This directory contains comprehensive examples demonstrating the use of the rustworkx backend in GraphWorkflow. Rustworkx provides faster graph operations compared to NetworkX, especially for large graphs and complex operations.

Installation

Before running these examples, ensure rustworkx is installed:

pip install rustworkx

If rustworkx is not installed, GraphWorkflow will automatically fallback to NetworkX backend.

Examples Overview

01_basic_usage.py

Basic example showing how to use rustworkx backend with GraphWorkflow. Demonstrates simple linear workflow creation and execution.

Key Concepts:

• Initializing GraphWorkflow with rustworkx backend
• Adding agents and creating edges
• Running a workflow

02_backend_comparison.py

Compares NetworkX and Rustworkx backends side-by-side, showing performance differences and functional equivalence.

Key Concepts:

• Backend comparison
• Performance metrics
• Functional equivalence verification

03_fan_out_fan_in_patterns.py

Demonstrates parallel processing patterns: fan-out (one-to-many) and fan-in (many-to-one) connections.

Key Concepts:

• Fan-out pattern: add_edges_from_source()
• Fan-in pattern: add_edges_to_target()
• Parallel execution optimization

04_complex_workflow.py

Shows a complex multi-layer workflow with multiple parallel branches and convergence points.

Key Concepts:

• Multi-layer workflows
• Parallel chains: add_parallel_chain()
• Complex graph structures

05_performance_benchmark.py

Benchmarks performance differences between NetworkX and Rustworkx for various graph sizes and structures.

Key Concepts:

• Performance benchmarking
• Scalability testing
• Different graph topologies (chain, tree)

06_error_handling.py

Demonstrates error handling and graceful fallback behavior when rustworkx is unavailable.

Key Concepts:

• Error handling
• Automatic fallback to NetworkX
• Backend availability checking

07_large_scale_workflow.py

Demonstrates rustworkx's efficiency with large-scale workflows containing many agents.

Key Concepts:

• Large-scale workflows
• Performance with many nodes/edges
• Complex interconnections

08_parallel_chain_example.py

Detailed example of the parallel chain pattern creating a full mesh connection.

Key Concepts:

• Parallel chain pattern
• Full mesh connections
• Maximum parallelization

09_workflow_validation.py

Shows workflow validation features including cycle detection, isolated nodes, and auto-fixing.

Key Concepts:

• Workflow validation
• Cycle detection
• Auto-fixing capabilities

10_real_world_scenario.py

A realistic market research workflow demonstrating real-world agent coordination scenarios.

Key Concepts:

• Real-world use case
• Complex multi-phase workflow
• Practical application

Quick Start

Run any example:

python 01_basic_usage.py

Backend Selection

To use rustworkx backend:

workflow = GraphWorkflow(
    backend="rustworkx",  # Use rustworkx
    # ... other parameters
)

To use NetworkX backend (default):

workflow = GraphWorkflow(
    backend="networkx",  # Or omit for default
    # ... other parameters
)

Performance Benefits

Rustworkx provides performance benefits especially for:

• Large graphs (100+ nodes)
• Complex operations (topological sorting, cycle detection)
• Frequent graph modifications (adding/removing nodes/edges)

Key Differences

While both backends are functionally equivalent, rustworkx:

• Uses integer indices internally (abstracted away)
• Provides faster graph operations
• Better memory efficiency for large graphs
• Maintains full compatibility with GraphWorkflow API

Notes

• Both backends produce identical results
• Rustworkx automatically falls back to NetworkX if not installed
• All GraphWorkflow features work with both backends
• Performance gains become more significant with larger graphs

Requirements

• swarms package
• rustworkx (optional, for rustworkx backend)
• networkx (always available, default backend)

Contributing

Feel free to add more examples demonstrating rustworkx capabilities or specific use cases!