Book Image

Hands-On Graph Analytics with Neo4j

By : Estelle Scifo
Book Image

Hands-On Graph Analytics with Neo4j

By: Estelle Scifo

Overview of this book

Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data.
Table of Contents (18 chapters)
1
Section 1: Graph Modeling with Neo4j
5
Section 2: Graph Algorithms
10
Section 3: Machine Learning on Graphs
14
Section 4: Neo4j for Production

Creating a full-stack web application using Python and Graph Object Mappers

There are different ways to programmatically interact with Neo4j. In the previous chapters, we used the Neo4j Python driver, from which we have been able to execute Cypher queries and retrieve the results, especially for creating DataFrames in a data science context. In the context of a web application, manually writing a Cypher query each time we want our program to perform an action on the graph would be a very time-consuming and laborious task involving repeating code. Fortunately, Graph Object Mappers (GOMs) have been created to interface Python code to Neo4j without us having to write a single Cypher query. In this section, we are going to use the neomodel package and use it alongside Flask to build a web application that displays information from Neo4j.

Our context is similar to GitHub: we have users that can own and/or contribute to repositories.

Toying with neomodel

neomodel is a Graph Object Mapper for...