NetworkX-Temporal is a Python package that extends the popular NetworkX library to dynamic graphs, enabling the modeling and analysis of time-evolving complex systems. As core features, it provides ways to generate, slice and visualize graphs as sequences of snapshots, transform or convert between different representations and formats, and compute temporal metrics and properties. It is designed to be flexible and easily extensible, suiting a wide range of applications, and may serve as a hub for temporal graph algorithm implementations. We present its design and implementation, elaborate on its key features, and describe some use cases to illustrate its capabilities.
NetworkX-Temporal: Building, manipulating, and analyzing dynamic graph structures
Nelson Aloysio Reis de Almeida Passos;Emanuele Carlini;Salvatore Trani
2025-01-01
Abstract
NetworkX-Temporal is a Python package that extends the popular NetworkX library to dynamic graphs, enabling the modeling and analysis of time-evolving complex systems. As core features, it provides ways to generate, slice and visualize graphs as sequences of snapshots, transform or convert between different representations and formats, and compute temporal metrics and properties. It is designed to be flexible and easily extensible, suiting a wide range of applications, and may serve as a hub for temporal graph algorithm implementations. We present its design and implementation, elaborate on its key features, and describe some use cases to illustrate its capabilities.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


