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NVDataModels Nautobot App

Features

This app provides the tools necessary to model NVIDIA components in Nautobot.

This app provides the following models:

  • NVLinkDomain
  • NVLinkDomainMembership
  • ResourceBlock
  • ResourceBlockMembership

Installation

Once the project is mature, installing this app will follow the standard process for installing any Nautobot app:

  1. Add nautobot-nvdatamodels to Nautobot's pyproject.toml
  2. Add nautobot_nvdatamodels to PLUGINS in nautobot_config.py

Currently, there are no plugin configuration options to add to PLUGINS_CONFIG in nautobot_config.py.

Development Environment Setup

Prerequisites

This project requires Docker, Docker Compose, and uv.

On macOS, use homebrew to install Docker, Docker Compose, and uv:

brew install --cask docker
brew install docker-compose uv

Setup

  1. Clone this project locally.

  2. Install dependencies.

    uv sync --all-extras
    
  3. Build image.

    invoke build
    
  4. Start containers.

    invoke start
    

The first time you start the containers with a fresh database, it will take 1-2 minutes for the Nautobot container to come up. Check progress by tailing the logs:

invoke logs -f  # <Ctrl-C> to stop

To enable automatic linting and formatting on file save, install the ruff VSCode plugin.

Once it's up, access the development server at http://localhost:8080.

Tips

Changes to code will auto-reload the worker for quick iteration. Tail the worker's logs for easier debugging:

invoke logs -f -s worker  # <Ctrl-C> to stop

If you're working with jobs, it's convenient to enable all jobs (which are disabled by default):

invoke enable-jobs  # Idempotently enables all disabled jobs, if any

If you're developing a job and need to re-run it often for testing, consider this approach:

  1. Run the job once in the GUI.

  2. Copy the JobResult's UUID.

  3. Re-run the job with the same parameters from the CLI:

    invoke rerun-job <job-result-uuid>
    

This is not only faster than the GUI-only method, but also gives you the option to feed debug output directly into AI agents, if you use an AI-assisted IDE like Cursor.

It's often helpful to populate Nautobot with dummy data for testing:

invoke cli
nautobot-server generate_test_data

See all available commands with:

invoke --help

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