Through this short tutorial, you will learn how to install Memgraph, connect to it from a Jupyter Notebook and perform data analysis using graph algorithms. You can find the original Jupyter Notebook in our open-source GitHub repository.
If at any point you experience problems with this tutorial or something is unclear to you, reach out on our Discord server. The dataset from this tutorial is also available in the form of a Playground sandbox which you can query from your browser.
We will be using the GQLAlchemy object graph mapper (OGM) to connect to Memgraph and execute Cypher queries easily. GQLAlchemy also serves as a Python driver/client for Memgraph. You can install it using:
Maybe you got confused when I mentioned Cypher. You can think of Cypher as SQL for graph databases. It contains many of the same language constructs like CREATE, UPDATE, DELETE… and it’s used to query the database.
We are going to create Python classes that will represent our graph schema. This way, all the objects that are returned from Memgraph will be of the correct type if the class definition can be found.