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This allows you to fully refresh a model from the console. Full-refresh/backfill is a common task. Using Airflow parameters makes this easy. Without this, you'd have to trigger an entire deployment. In our setup, company analysts manage their models without modifying the DAG code. This empowers such users. Example of usage: ```python with DAG( dag_id="jaffle", params={"full_refresh": Param(default=False, type="boolean")}, render_template_as_native_obj=True ): task = DbtTaskGroup( operator_args={"full_refresh": "{{ params.get('full_refresh') }}", "install_deps": True}, ) ``` Closes: #151
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