Flask, a popular Python web framework, has many tutorials available online which use an SQL database to store information about the website’s users and their activities. While SQL is a great tool for storing information such as usernames and passwords, it is not so great at allowing you to find connections among your users for the purposes of enhancing your website’s social experience.
In this tutorial, we will replace SQL with Neo4j, an open source graph database, in order to build a simple microblog application. We will incorporate social features that are otherwise too complex to model and express in SQL, including recommending similar users to the logged-in user, along with displaying similarities between two users when one user visits another user’s profile.
Prior to diving into the application, we will go over some Neo4j basics including data modeling and querying—just enough to get us comfortable building an application on top of Neo4j.
Nicole White grew up in Kansas City, Missouri. She spent four years at LSU in Baton Rouge, Louisiana where she earned a degree in economics with a minor in mathematics. She then went to the University of Texas at Austin, where she received her master’s degree in analytics. It was during this time that she found Neo4j and began exploring its capabilities. When she’s not graphing all the things, she spends her time playing card games and board games.
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