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v0.1.0

This is the very first release of Debby 🥳

Our goal with this release is to validate our check writing framework and get our infrastructure up and running.

As a result, this first release includes just a single simple check check_model_descriptions. Hey, you gotta start somewhere! Over the next few releases we'll be working towards supporting the same set of checks as similar projects like dbt-checkpoint and dbt-project-evaluator.

We've also set up our supported deployment targets: GitHub actions, pre-commit hooks, and directly installing from PyPi. Of course there's also our documentation site debbyapp.com/docs, which you're using right now.

Lastly, we've created a demo project for viewing a live version of Debby, which includes both the GitHub action and the pre-commit installation paths. You can use the demo project to get a feel for what Debby looks like in production.

Supported checks

The initial release of Debby includes a single check check_model_descriptions.

As we add more checks they'll be listed on our documentation site

https://www.debbyapp.com/docs/checks.

Each check also has a permanent link for documentation about the check. The documentation covers topics like how to fix the check if it's failing, why you might want to use the check, as well as the source code that powers the check. For example the check_model_descriptions check is documented here:

https://www.debbyapp.com/docs/checks/check_model_descriptions.

Supported deployment targets

Debby can be deployed in three different ways:

  1. Using a GitHub action directly in your repository.
  2. Using a pre-commit hook in your repository.
  3. Downloading a Python package from PyPI and running our CLI directly.

Installing with GitHub actions

We released a new GitHub action that can be used to run Debby during a CI process. The GitHub action is designed to make it as simple as possible for users to install and run Debby against their dbt projects.

Here's a simple example of using the GitHub action.

# .github/workflows/debby.yaml

name: Debby
on: [push]

jobs:
  debby:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      # install the dbt adapter you're using
      - run: pip install dbt-core dbt-snowflake

      # generate a manifest.json for debby to use
      - run: dbt parse

      # run the action
      - uses: tjwaterman99/debby-actions@v0.1.0

For more information on installing Debby as a GitHub action, see the related install instructions.

Installing with a pre-commit hook

We released a new pre-commit hook that can be used to run Debby locally, whenever a user modifies a file in their dbt project. The pre-commit action is designed to provide feedback as fast as possible to users.

To add a pre-commit hook that runs debby, you can modify your .pre-commit-config.yaml file to include the following.

# .pre-commit-config.yaml
repos:
  - repo: https://www.github.com/tjwaterman99/debby-pre-commit
    rev: v0.1.0
    hooks:
      - id: debby

For more information on installing Debby as a pre-commit hook, see the related install instructions.

Installing from PyPI

The Debby cli is now available for download from PyPI. To install the cli use pip, or any other Python package manager. For example:

pip install debby-cli

The debby-cli package installs an executable named debby. For instructions on using the cli, use the --help flag.

debby --help

Warning

Debby does not support a stable Python API, at least for its initial releases. We may release breaking changes to Python objects within the package at any time.

For more information on installing Debby as a command line tool, see the related install instructions.

Demo site

We've created a demo GitHub repository for illustrating Debby in action.

https://github.com/tjwaterman99/debby-demo

We expect this project to get more developed as we start adding support for more complicated checks.