neo4j-viz 0.3.1

A simple graph visualization tool

Graph Visualization for Python by Neo4j

neo4j-viz is a Python package for creating interactive graph visualizations.

The output is of type IPython.display.HTML and can be viewed directly in a Jupyter Notebook or Streamlit application. Alternatively, you can export the output to a file and view it in a web browser.

The package wraps the Neo4j Visualization JavaScript library (NVL).

[!WARNING] This package is still in development and the API is subject to change.

Some notable features

• Easy to import graphs represented as:
  • projections in the Neo4j Graph Data Science (GDS) library
  • graphs from Neo4j query results
  • pandas DataFrames
• Node features:
  • Sizing
  • Colors
  • Captions
  • Pinning
  • On hover tooltip
• Relationship features:
  • Colors
  • Captions
  • On hover tooltip
• Graph features:
  • Zooming
  • Panning
  • Moving nodes
  • Using different layouts
• Additional convenience functionality for:
  • Resizing nodes, optionally including scale normalization
  • Coloring nodes based on a property
  • Toggle whether nodes should be pinned or not

Please note that this list is by no means exhaustive.

Getting started

Installation

Simply install with pip:

pip install neo4j-viz

Basic usage

We will use a small toy graph representing the purchase history of a few people and products.

We start by instantiating the Nodes and Relationships we want in our graph. The only mandatory fields for a node are the "id", and "source" and "target" for a relationship. But the other fields can optionally be used to customize the appearance of the nodes and relationships in the visualization.

Lastly we create a VisualizationGraph object with the nodes and relationships we created, and call its render method to display the graph.

from neo4j_viz import Node, Relationship, VisualizationGraph

nodes = [
    Node(id=0, size=10, caption="Person"),
    Node(id=1, size=10, caption="Product"),
    Node(id=2, size=20, caption="Product"),
    Node(id=3, size=10, caption="Person"),
    Node(id=4, size=10, caption="Product"),
]
relationships = [
    Relationship(
        source=0,
        target=1,
        caption="BUYS",
    ),
    Relationship(
        source=0,
        target=2,
        caption="BUYS",
    ),
    Relationship(
        source=3,
        target=2,
        caption="BUYS",
    ),
]

VG = VisualizationGraph(nodes=nodes, relationships=relationships)

VG.render()

This will return a IPython.display.HTML object that can be rendered in a Jupyter Notebook or streamlit application.

Please refer to the documentation for more details on the API and usage.

Examples

For more extensive examples, including how to import graphs from Neo4j GDS projections and Pandas DataFrames, checkout the tutorials chapter in the documentation.