= networkx-neo4j

This library provides NetworkX API for https://github.com/neo4j/graph-data-science/[Neo4j Graph Data Science^]. You should be able to use it as you would NetworkX but algorithms will run against Neo4j.

== Dependencies

• ≥ Neo4j 4.x
• Graph Data Science Library Plugin
• APOC Plugin
• ≥ Python 3.6
• ≥ neo4j-driver 4.x

== Installation

You can install the library by running the following command:

[source, bash]

pip install networkx-neo4j

You'll also need to install APOC and the Graph Algorithms library.

image:images/plugin.jpg[plugin] image:images/gds.jpg[gds]

== Usage

Here's how you use it.

First let's import our libraries and create an instance of the Neo4j driver:

[source, python]

from neo4j import GraphDatabase import nxneo4j as nx

driver = GraphDatabase.driver(uri="bolt://localhost",auth=("neo4j","your_password"))

For undirected Graphs: [source, python]

G = nx.Graph(driver)

For directed Graphs: [source, python]

G = nx.DiGraph(driver)

The available functions in nxneo4j are: [source, python]

ADD ONE NODE

G.add_node(node) node: str, int

G.add_node(1)

ADD MULTIPLE NODES

G.add_nodes_from(value) values: list

G.add_nodes_from([1, 2, 3, 4])

ADD ONE EDGE

G.add_edge(node1,node2) node1: str, int node2: str, int

G.add_edge(1,2)

#ADD MULTIPLE EDGES G.add_edges_from(values) values: list of tuples

G.add_edges_from([(1, 2),(2, 3),(3, 4)])

The available algoritms in nxneo4j are: [source, python]

nx.betweenness_centrality(G) {3: 4.0, 4: 3.0, 1: 0.0, 2: 0.0, 5: 0.0}

nx.closeness_centrality(G) {3: 0.8, 4: 0.6666666666666666, 1: 0.5714285714285714, 2: 0.5714285714285714, 5: 0.4444444444444444}

nx.pagerank(G) {3: 1.4170146573314513, 4: 1.0629939728840803, 1: 0.9591085771210682, 2: 0.9591085771210682, 5: 0.6017724112363687}

nx.triangles(G) {1: 1, 2: 1, 3: 1, 4: 0, 5: 0}

nx.clustering(G) {1: 1.0, 2: 1.0, 3: 0.3333333333333333, 4: 0.0, 5: 0.0}

list(nx.community.label_propagation_communities(G)) [{1, 2, 3, 4, 5}]

nx.shortest_path(G, source=1, target=5) [1, 3, 4, 5]

== Credits Yusuf Baktir Mark Needham David Jablonski