README.md

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Description

This application uses Python to extract data from various sources and load it into a Neo4j database. It is designed to be run in a Docker container for easy setup and deployment. This contains a simple class that extracts data from a few different file types and creates Dict's The remaining is a structure to load the data into a Neo4j database and follow the applictaion model

Getting Started

Dependencies

• Docker
• Docker Compose (optional, for simplified multi-container setup)
• Python 3.8
• Neo4j (for local development or separate container deployment)

Installing

• Clone this repository.
• Ensure Docker and Docker Compose (if using) are installed on your system.

Running the Application

Running Separately

If you prefer to run Neo4j and the Python application separately, you can do so by executing each container independently.

1. Start Neo4j container:

   docker run \
       --name neo4j \
       -p7474:7474 -p7687:7687 \
       -d \
       -v $HOME/neo4j/data:/data \
       -v $HOME/neo4j/logs:/logs \
       -v $HOME/neo4j/import:/var/lib/neo4j/import \
       -v $HOME/neo4j/plugins:/plugins \
       --env NEO4J_AUTH=neo4j/password \
       neo4j:latest

2. Build and run the Python application container:

   docker build -t py-neo4j-app .
   docker run -p 4000:80 --net=host py-neo4j-app

   Ensure that the environment variables in the docker run command match the settings of your Neo4j container.

Usage

After starting the application using either method, access the Python app at http://localhost:4000 and the Neo4j browser interface at http://localhost:7474.