
Build a Python web app with Flask and Neo4j, focusing on a graph database to power a blog with social features, including user registration, posting, and social recommendations.
Learn cypher basics: use the match clause to pattern nodes and relationships, apply node labels and relationship types, assign identifiers, return results, and collect movies per person.
Learn how to pass Python variables to Flask templates with render_template, set up a templates directory, and render strings, lists, and lists of dictionaries in HTML.
Apply uniqueness constraints on user name, post id, and tag name by creating constraints on node label property pairs at application startup, producing indexes for efficient lookups.
Finish implementing user registration by defining a user class with find and register methods using graph to locate and create user nodes, encrypting passwords, flashing messages, and redirecting to login.
Finish implementing the like post feature by validating user login and creating a unique like relationship between user and post in Neo4j, then redirect to the referer page.
Deploy your Flask app to Heroku by creating a proc file and a requirements.txt, using the Heroku port from the port environment variable, and disabling debug mode.
Deploy to Heroku by pushing code, configuring graphene db add-on, and using an environment variable for the database URL. Confirm cloud deployment and test with a live app URL.
In this Building Web Apps Using Flask and Neo4j training course, expert author Nicole White will teach you how to incorporate graph databases into your web applications. This course is designed for the absolute beginner, meaning no previous experience with Flask or Neo4j is required.
You will start by learning how to install Neo4j and set up your project. From there, Nicole will teach you the basics of Neo4j, Flask, and Py2neo. She will then walk you through building a microblogging application from scratch, where you will learn how to register and login users, add posts, and display posts. This video tutorial also covers social recommendations, including recommending similar users and commonalities between two users. Finally, you will learn about scaling considerations and how to deploy your project to Heroku.
Once you have completed this computer based training course, you will have learned how to incorporate Neo4j into your own web applications. Working files are included, allowing you to follow along with the author throughout the lessons.