When Mark Needham first started learning Python he came across the NetworkX library and always enjoyed using it to run graph algorithms against my toy datasets.
Nowadays Neo4j has its own Graph Algorithms library but we have to call that via Cypher procedures which isn’t quite as nice. Mark wanted to fix that.
As a result, a few months ago he started writing a NetworkX-esque API that would provide a nice wrapper around Neo4j’s algorithms. In this talk he’d like to show off the library and how easy it is to use the networkx function calls that you’re used to without having to worry whether your graph will fit in memory in your Python program.
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A NetworkX-esque API for Neo4j Graph Algorithms
Mark is a graph advocate and field engineer for Neo Technology, the company behind the Neo4j graph database. As a field engineer, Mark helps customers embrace graph data and Neo4j by building sophisticated solutions to challenging data problems.