Knowledge Graph Construction Through Neo4j

Install Additional Required Libraries

In order to communicate with neo4j Desktop graph database, the neo4j_python_driver need to be installed:

pip install neo4j

Connect to Neo4j via DACKAR Py2Neo Module

  • Set up Neo4j import folder path

    This directory is used to store data files intended for bulk import operations. The location of this directory can be configured in the Neo4j configuration file (neo4j.conf). By default, the import directory is located at: $NEO4J_HOME/import. Here, $NEO4J_HOME represents the root directory of your Neo4j installation. To change the import directory, you can modify the dbms.directories.import setting in the neo4j.conf file. For example:

    Make sure to replace /path/to/your/import/directory with the actual path you want to use for your import files. After making changes to the neo4j.conf file, you will need to restart the Neo4j server for the changes to take effect.

  • Alternative way to set up Neo4j import folder path

    Open the settings, and replace dbms.directories.import with the actual path you want to use for your import files.

    Set up Neo4j import folder path

  • Start Neo4j desktop DBMS, set password if needed, this password will be used in Python driver to connect to DBMS database.

    Neo4j Desktop Graph Database Management System

  • Load DACKAR Py2Neo module to load csv files into Neo4j DBMS.

    from dackar.knowledge_graph.py2neo import Py2Neo
# Create python to neo4j driver
uri = "neo4j://localhost:7687" # for a cluster
pwd = "123456789" # user need to provide the DBMS database password
py2neo = Py2Neo(uri=uri, user='neo4j', pwd=pwd)

# clean up the DBMS
py2neo.reset()

# Load node data
file_path = './test_nodes.csv'
# node label
label = 'MBSE'
# node attributes: keys, values are corresponding to neo4j node attributes and csv column names, respectively
attribute = {'nodeId':'nodeId', 'label':'label', 'ID':'ID', 'type':'type'}
# API to load csv files to create nodes in neo4j
py2neo.load_csv_for_nodes(file_path, label, attribute)
# Load relationship data
file_path = 'test_edges.csv'
l1='MBSE' # label for source node
# node attributes: keys, values are corresponding to neo4j node attributes and csv column names, respectively
p1={'nodeId':'sourceNodeId'}
# label for second node
l2='MBSE'
# node attributes: keys, values are corresponding to neo4j node attributes and csv column names, respectively
p2 ={'nodeId':'targetNodeId'}
# label for neo4j edge
lr = 'MBSE_link'
# edge attributes: keys, values are corresponding to neo4j node attributes and csv column names, respectively
pr = {'prop':'type'}
# API to load csv files to create relations in neo4j
py2neo.load_csv_for_relations(file_path, l1, p1, l2, p2, lr, pr)