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The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks. It is recommended to explore them. All of the commands and features supported by graph notebook are explained in detail with examples within the sample notebooks. You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder.
Features
- Visualizing Gremlin queries
- Visualizing openCypher queries
- Visualizing SPARQL queries
- We encourage others to contribute configurations they find useful
- Executes a SPARQL query against your configured database endpoint
- Executes a Gremlin query against your database using web sockets. The results are similar to those a Gremlin console would return
Project Samples
