NPAP: Network Partitioning and Aggregation Package for Python

2026-05-12

AI Summary

This work addresses the high spatial complexity and low computational efficiency inherent in large-scale network graph analysis by proposing a two-stage network simplification method that explicitly decouples node partitioning from network aggregation. Built upon NetworkX, the authors develop a modular and extensible open-source Python library employing a strategy-pattern architecture, which enables users to flexibly register custom partitioning and aggregation strategies. The implementation includes 13 partitioning strategies and 2 aggregation templates, balancing generality with domain-specific adaptability. Empirical validation in real-world applications—such as power systems—demonstrates the approach’s computational efficiency and practical engineering utility.

Abstract

NPAP (Network Partitioning and Aggregation Package) is an open-source Python library for reducing the spatial complexity of network graphs. Built on NetworkX, it provides an accessible standalone package designed to be readily integrated with other software and frameworks. Instead of treating the spatial reduction process as a single action, NPAP explicitly splits it into two distinct steps: partitioning, which assigns vertices (nodes) to groups (clusters), and aggregation, which reduces the network based on a given assignment. NPAP's strategy pattern architecture allows users to employ and register custom partitioning and aggregation strategies seamlessly without modifying the core code. Currently, NPAP provides 13 different partitioning strategies and two pre-defined aggregation profiles. Although initially developed with a focus on power systems, its architecture is general-purpose and applicable to any network graph.

Problem

• network partitioning
• graph aggregation
• spatial complexity reduction
• network simplification
• graph clustering

Innovation

• network partitioning
• graph aggregation
• strategy pattern
• spatial complexity reduction
• modular architecture