Quickstart#
Navigate to your dbt project's directory. This should be a folder that contains a dbt_project.yml
file.
Parse your dbt proejct#
Parsing your dbt project generates a manifest.json
artifact, which Checkers uses to understand the structure of your dbt project.
Many other dbt commands also generate a manifest.json
, including dbt build
, dbt test
, etc. But we recommend using dbt parse
as it usually takes just a few seconds.
Generate default config#
The default configuration file is called linter.toml
. You can use it to enable and disable certain checks. It can also be used to pass parameters to individual tests, controlling various aspects of how they run.
The init
command will also generate an example linter.py
file. This file contains a custom lint check. For more information on writing custom checks, see the related user guide.
Run the checks#
The run command will scan your dbt project for any errors, and print its results to the console.
PASS check_model_has_description my_first_dbt_model
PASS check_model_has_description my_second_dbt_model
By default, the run
command will return a non-zero exit code if it detects any models that fail any checks. This enables you to use Checkers as part of a CI process, so that any changes to your dbt project which introduce error are blocked before they make it into production.
For help on configuring how Checkers run, use the following command:
Next steps#
- Review the list of builtin checks
- Consult the configuration details page for more information on enabling or disabling various checks