Thank you for considering spending your time contributing to the Splunk 3D Graph Network Topology Visualization. 🚀
Whether you're interested in bug-hunting, documentation, or creating entirely new features, this document will help and guide you through the process.
If you're seeing some unexpected behavior with this project, please create an issue on GitHub selecting the opportune template and providing requested information.
We ❤️ to see your fixes via pull requests!
To create a pull request:
- Fork the project
- Create a branch for the issue
- Make your changes on your branch
- Thoroughly test your changes
- Open a pull request
Remember:
- Address an issue per branch
A GitHub Action is provided to:
- Bump the app version
- Create a release
This action can be manually triggered by clicking on Actions / Manual Release / Run Workflow and by providing:
- Bump part - Either major, minor or patch
- (Optional) Changelog notes - By default all commit messages beginning from the last release are included
NOTE Action available to all users with
Writerole at least
The recommended local development environment is based on Docker. After the setup, the local Splunk Web will be available on http://localhost:8000 with Splunk Machine Learning Toolkit (MLTK) and the Python for Scientific Computing for Linux installed.
- Docker
Create a .env file in the root of the repository. Don't worry, it is part of .gitignore.
cp .env.sample .env
Enter your Splunkbase Username and Password there to install dependencies such as the Splunk MLTK via URL.
To setup your development environment, run
make setup
This will:
- Install App dependencies
- Configure them in your local environment
- Run docker-compose up to start the local environment
To execute tests locally, run
make tests