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A tool to allow easy integration between data enhancement apis and graphdatabase

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intel_grapher

Requirements

Docker [if you want to run neo4j locally and easily] Requests py2neo

Getting started

First install neo4j using docker onto your system

'''docker run
--publish=7474:7474 --publish=7687:7687
--volume=$HOME/neo4j/data:/data
neo4j'''

Login and it'll force you to change the password. For testing and dev purposes we just choose 'password' since it will at this time only run locally

To test data ingestion, run the tester.py file and it should consume some of the data

NEXT STEPS

Create the API end-points based on the nodes and relationships Develop some basic API queries that can be used Add additional plugins Build some form of front end to interact and query the data

Plugin Design

To help facilitate the creation of different plugins, here are the recommended structured and elements for each plugin: Plugins need to provide a means to collecting data, transforming it and querying it.

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A tool to allow easy integration between data enhancement apis and graphdatabase

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