Data Science & AI Workbench enables you to connect to the Neo4j graph database platform to work with data stored while in a notebook session.To access Neo4j within the platform, you’ll need to pip install the required driver using the following command:
Any packages you install from the command line are available during the current session only. If you want them to persist, add them to the project’s anaconda-project.yml file. For more information, see Project configurations.
After you’ve installed the required driver, you can then use code such as this to access Neo4j from within a notebook session:
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from neo4j import GraphDatabaseimport json"""Get credentials from Kubernetes. The credentials were set up as a dictionary. For example:{ "username": "USERNAME", "password": "PASSWORD"}"""credentials = Nonewith open('/var/run/secrets/user_credentials/neo4j_credentials') as f: credentials = json.load(f)# Verify that the credentials were pulled correctlyif credentials: # Setup the connection uri = f"bolt://{credentials.get('host_name')}:7687" driver = GraphDatabase.driver( uri, auth=( credentials.get('username'), credentials.get('password') ) ) # Define function that queries the database def print_info(tx): for record in tx.run( 'MATCH (tom:Person {name: "Tom Hanks"})-' '[:ACTED_IN]->(tomHanksMovies) RETURN tom,tomHanksMovies' ): # Print out the records that it finds print(record) # Scope the session and call the query with driver.session() as session: session.read_transaction(print_info)
See Secrets for information about adding credentials to the platform, to make them available in your projects. Any secrets you add will be available across all sessions and deployments associated with your user account.
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