dbt-cloud-jobs 0.0.1

Version control your dbt Cloud jobs with YML.

dbt-cloud-jobs

Version control your dbt Cloud jobs with YML.

Installation

pip install dbt-cloud-jobs

Quickstart

1. Create an API token in dbt Cloud:

   • Generate a service account token, make sure to grant the Jobs Admin permission set.
   • If you do not have access to create a service account token you can create a User API token. Note that the service account method is preferred.

2. Set an environment variables with the value of the token:

   export DBT_API_TOKEN="<VALUE_FROM_PREVIOUS_STEP>"
   

3. Import your existing dbt Cloud jobs:

   dbt_cloud_jobs --import --account_id 123456 --file dbt_cloud_jobs.yml
   

4. Edit the definition of your jobs in dbt_cloud_jobs.yml.

5. Sync the updated definitions to dbt Cloud:

   dbt_cloud_jobs --sync --file dbt_cloud_jobs.yml
   

Recommended usage in CI/CD

CI

In CI dbt_cloud_jobs should be used to verify that the provided YML file is valid. For example:

    - name: Install dbt_cloud_jobs
      run: pip install dbt_cloud_jobs

    - name: Validate `dbt_cloud_jobs.yml`
      run: dbt_cloud_jobs --validate --file dbt_cloud_jobs.yml

CD

In CD dbt_cloud_jobs should be used to sync the provided YML file to dbt Cloud. For example:

    - name: Install dbt_cloud_jobs
      run: pip install dbt_cloud_jobs

    - name: Sync `dbt_cloud_jobs.yml`
      run: dbt_cloud_jobs --sync --file dbt_cloud_jobs.yml

Development

Release

Trigger the Publish workflow, inputting the version to publish to PyPi. This workflow will:

• Publish the version to PyPi.
• Tag the HEAD commit of the main branches (tags visible here).
• Create a release (releases visible here).