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Graph Data Modeling in Python

You're reading from   Graph Data Modeling in Python A practical guide to curating, analyzing, and modeling data with graphs

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618035
Length 236 pages
Edition 1st Edition
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Authors (2):
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Gary Hutson Gary Hutson
Author Profile Icon Gary Hutson
Gary Hutson
Matt Jackson Matt Jackson
Author Profile Icon Matt Jackson
Matt Jackson
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Getting Started with Graph Data Modeling
2. Chapter 1: Introducing Graphs in the Real World FREE CHAPTER 3. Chapter 2: Working with Graph Data Models 4. Part 2: Making the Graph Transition
5. Chapter 3: Data Model Transformation – Relational to Graph Databases 6. Chapter 4: Building a Knowledge Graph 7. Part 3: Storing and Productionizing Graphs
8. Chapter 5: Working with Graph Databases 9. Chapter 6: Pipeline Development 10. Chapter 7: Refactoring and Evolving Schemas 11. Part 4: Graphing Like a Pro
12. Chapter 8: Perfect Projections 13. Chapter 9: Common Errors and Debugging 14. Index 15. Other Books You May Enjoy

Refactoring and Evolving Schemas

This chapter will spend some time discussing what makes a good schema and approaches to take if you need to refactor or change your schema. We will explore what and how entities can change in a graph database. This will then lead us to why you need to consider evolving schemas. Here, the focus will be on making your schema bulletproof when it comes to its evolution.

Following on from this, we will present a use case of Twitter circles, which will look at setting up your interface between Neo4j and Python (this is something we have extensively covered in other chapters), adding constraints to the Cypher queries we will write to build the graph data model in Neo4j, and some considerations you need to make pre-schema change concerning node and edgelist relationships. Then, we will change the schema with our hypothetical needs, without disrupting a live service. Finally, we will reflect on why the design of evolving schemas is pivotal for successful...

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