Talks - Mridul Seth, Erik Welch: NetworkX is Fast Now: Graph Analytics Unleashed

NetworkX is a 20-year-old pure Python graph analytics library with 50M monthly downloads on PyPI, offering zero dependencies and broad compatibility

Recent performance improvements through backend dispatching allow 100-1000x speedups without code changes, particularly using GPU acceleration via cuGraph

Three main open-source backends currently available:

• NXCuGraph (GPU acceleration with CUDA)
• Graph+ (CPU optimized)
• NXParallel (parallel processing using JobLib)

New caching system in NetworkX 3.3 allows storing converted graph representations for repeated operations, significantly reducing overhead

Backend implementations must pass NetworkX test suite for compatibility, providing free testing, documentation and API consistency

Experimental work exploring integration with graph databases for data persistence beyond memory-only operations

Performance improvements enable processing of much larger graphs - from minutes to seconds for operations like betweenness centrality

Focus on maintaining simple API and ease of use while adding scalability options

Community-governed project with no corporate ownership, emphasizing documentation and examples

Working toward standardized Graph API layer similar to Array API/DataFrame protocol for interoperability between different implementations