Major Feature Release: NetworkX Plotter API

[terapyon]

New Features

• High-level Plotter API: Direct NetworkX graph visualization without manual JSON conversion

  • Plotter.add_networkx() method for seamless graph rendering in JupyterLab
  • Support for all 4 NetworkX graph types: Graph, DiGraph, MultiGraph, MultiDiGraph
  • Automatic node/edge extraction with attribute preservation

• Custom Styling Support:

  • Node color mapping via attribute names or callable functions
  • Node label mapping with flexible attribute selection
  • Edge label mapping for relationship visualization
  • Automatic color scale detection (continuous vs. categorical)

• Layout Control:

  • 5 built-in layout algorithms: spring, kamada_kawai, spectral, circular, random
  • Custom layout function support
  • Existing position attribute detection
  • Automatic fallback with NaN/inf validation

• Multi-Graph Type Support:

  • Edge direction preservation for DiGraph (via metadata)
  • Edge key preservation for MultiGraph/MultiDiGraph
  • Multiple edge expansion into independent Edge objects
  • Automatic graph type detection and dispatch

API Examples

from net_vis import Plotter
import networkx as nx

# Basic visualization
G = nx.karate_club_graph()
plotter = Plotter(title="Karate Club Network")
plotter.add_networkx(G)

# Custom styling
plotter.add_networkx(G,
    node_color="club",
    node_label=lambda d: f"Node {d.get('name', '')}",
    layout='kamada_kawai'
)

Implementation Details

• NetworkXAdapter: 650+ lines of conversion logic with comprehensive type hints
• Test Coverage: 60+ test methods covering all public APIs
• Python 3.10+ type hints: Full type annotation support
• Comprehensive docstrings: All public methods documented

Compatibility

• NetworkX: 3.0+
• JupyterLab: 3.x and 4.x
• Python: 3.10+