rofrano/dgi repository overview

⁠Data Gravity Insights

This image contains and pre-installed version of Konveyor Data Gravity Insights. It comes complete with a Python 3.9 environment so that you can invite it as a command without needing Python on your system. This image supports both Intel and ARM base (Apple Silicon) systems.

⁠Usage

You will need a Neo4J server version 4.4.17. You can start one in a Docker container with the following command:

docker run -d --name neo4j \
     -p 7474:7474 \
     -p 7687:7687 \
     -v neo4j:/data \
     -e NEO4J_AUTH="neo4j/konveyor" \
     docker.io/neo4j:4.4.17

Normally you will need to have access to the local files that you want to process so you need to share your local folder with the container with -v $(pwd):/work -w /work. You will also need to inject a link to the Neo4J server like this: --link neo4j. Then just pass in the arguments to dig. Here is an example command:

docker run --rm -it --link neo4j -v $(pwd):/work -w /work dgi:1.0.0 --clear c2g --abstraction=class --input=doop-output

This will run the dgi command with the options --clear c2g --abstraction=class --input=doop-output.

⁠Support

To report a bug or just learn more about the project, please visit our GitHub repo: tackle-data-gravity-insights⁠