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Hands-On Graph Analytics with Neo4j

You're reading from   Hands-On Graph Analytics with Neo4j Perform graph processing and visualization techniques using connected data across your enterprise

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781839212611
Length 510 pages
Edition 1st Edition
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Author (1):
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Estelle Scifo Estelle Scifo
Author Profile Icon Estelle Scifo
Estelle Scifo
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Graph Modeling with Neo4j
2. Graph Databases FREE CHAPTER 3. The Cypher Query Language 4. Empowering Your Business with Pure Cypher 5. Section 2: Graph Algorithms
6. The Graph Data Science Library and Path Finding 7. Spatial Data 8. Node Importance 9. Community Detection and Similarity Measures 10. Section 3: Machine Learning on Graphs
11. Using Graph-based Features in Machine Learning 12. Predicting Relationships 13. Graph Embedding - from Graphs to Matrices 14. Section 4: Neo4j for Production
15. Using Neo4j in Your Web Application 16. Neo4j at Scale 17. Other Books You May Enjoy

Understanding GraphQL APIs by example – GitHub API v4

While in the previous section we used Python to build a full web application whose backend database is Neo4j, in this section, we will remove the dependency on Python and build an API directly accessible from the Neo4j server.

When building APIs, a very popular framework is Representational State Transfer (REST). Even though this approach is still possible with a graph database (check, for instance, the gREST project), a different approach is becoming more and more popular – GraphQL, a query language for API.

In order to understand GraphQL, we will again use the GitHub API. In previous chapters, we used the REST version (v3). However, v4 uses GraphQL, so we should build a few queries. To do so, we can go to https://developer.github.com/v4/explorer/, which is the traditional GraphQL playground. After providing GitHub login credentials, there is a two-part window; the left panel is where we will write the query, while the...

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