Getting Started

How to run dbt-bouncer

1. Generate dbt artifacts by running a dbt command:

   • dbt parse to generate a manifest.json artifact.
   • dbt docs generate to generate a catalog.json artifact (necessary if you are using catalog checks).

2. Create a dbt-bouncer.yml config file, details here.

3. Run dbt-bouncer to validate that your conventions are being maintained.

Python

Install from pypi.org:

pip install dbt-bouncer

Run:

dbt-bouncer --config-file <PATH_TO_CONFIG_FILE>

Running dbt-bouncer (X.X.X)...
Loaded config from dbt-bouncer-example.yml...
Validating conf...

GitHub Actions

Run dbt-bouncer as part of your CI pipeline:

steps:
    ...

    - uses: godatadriven/dbt-bouncer@vX.X
      with:
        config-file: ./<PATH_TO_CONFIG_FILE>
        output-file: results.json # optional, default does not save a results file
        send-pr-comment: true # optional, defaults to true

    ...

We recommend pinning both a major and minor version number.

Docker

Run dbt-bouncer via Docker:

docker run --rm \
    --volume "$PWD":/app \
    ghcr.io/godatadriven/dbt-bouncer:vX.X.X \
    --config-file /app/<PATH_TO_CONFIG_FILE>

Pex

You can also run the .pex (Python EXecutable) artifact directly once you have a python executable (3.8 -> 3.12) installed:

wget https://github.com/godatadriven/dbt-bouncer/releases/download/vX.X.X/dbt-bouncer.pex -O dbt-bouncer.pex

python dbt-bouncer.pex --config-file $PWD/<PATH_TO_CONFIG_FILE>