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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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 Scifo Scifo
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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

Discovering the Neo4j Python driver

Python is officially supported by Neo4j, who provides a driver to connect to a Neo4j graph from Python at https://github.com/neo4j/neo4j-python-driver.

It can be installed through the pip Python package manager:

pip install neo4j
# or
conda install -c conda-forge neo4j
The code for this section is available in a Jupyter notebook: Neo4j_Python_Driver.ipynb.

In order to use this database, the first step is the connection definition, which requires the active graph URI and the authentication parameters. bolt is a client-server communication protocol designed by Neo4j. The port used by the bolt protocol for your active database can be found in the Management area of your graph in Neo4j Desktop, in the Details tab:

from neo4j import GraphDatabase driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "<YOUR_PASSWORD>"))
In the case of misconfiguration, you will get the following:
  • ServiceUnavailable...
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