https://github.com/bydevmar/jupyter_neo4j

This repository demonstrates Python integration with Jupyter Notebooks and Neo4j, showcasing a basic social media network model and database interaction.
https://github.com/bydevmar/jupyter_neo4j

jupyter-lab jupyter-notebook neo4j neo4j-database python3

Last synced: 2 days ago
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This repository demonstrates Python integration with Jupyter Notebooks and Neo4j, showcasing a basic social media network model and database interaction.

• Host: GitHub
• URL: https://github.com/bydevmar/jupyter_neo4j
• Owner: bydevmar
• Created: 2024-03-31T17:05:39.000Z (9 months ago)
• Default Branch: bydev
• Last Pushed: 2024-05-05T20:14:45.000Z (8 months ago)
• Last Synced: 2024-11-03T08:41:57.363Z (about 2 months ago)
• Topics: jupyter-lab, jupyter-notebook, neo4j, neo4j-database, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 6.84 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Python Jupyter Binding with Neo4j

## Introduction

This project demonstrates how to use Python within a Jupyter Notebook environment to interact with Neo4j, a popular graph database. In this project, we create a simple social media network model using Python classes and then interact with a Neo4j database to represent and query this model.

## Requirements

- Python

- Jupyter Notebook

- Neo4j

- py2neo library

## Getting Started

1. Install Python, Jupyter Notebook, and Neo4j on your system.

2. Install the py2neo library using `pip install py2neo`.

3. Clone this repository to your local machine.

4. Open the Jupyter Notebook file (`notebook.ipynb`) in your Jupyter environment.

## Usage

1. Import the required modules and establish a connection to Neo4j.

2. Create classes for User, Post, and SocialMediaPlatform.

3. Create instances of users, social media platforms, and posts.

4. Create nodes for social media platforms, users, and posts in the Neo4j database.

5. Establish relationships between users and platforms, and users and posts.

6. Execute queries to retrieve information from the Neo4j database.

## Conclusion

This project serves as a practical demonstration of using Python with Jupyter Notebook for interacting with a Neo4j graph database. Feel free to explore and expand upon the provided codebase to suit your specific requirements.

For more information, refer to the official documentation of Neo4j and py2neo.