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Generate DAGs from yml

You have the option to write out your DAGs in python or you can write them using yml and then have dbt-coves generate the python DAG for you.

Configure config.yml

This configuration is for the dbt-coves generate airflow-dags command which generates the DAGs from your yml files. Visit the dbt-coves docs for the full dbt-coves configuration settings.

dbt-coves will read settings from <dbt_project_path>/.dbt_coves/config.yml . We must create these files in order for dbt-coves to function.

Step 1: Create the .dbt-coves folder at the root of your dbt project (where the dbt_project.yml file is located). Then create a file called config.yml inside of .dbt-coves .


Datacoves' recommended dbt project location is transform/ eg) transform/.dbt-coves/config.yml . This will require some minor refactoring and ensuring that the dbt project path in your environment settings reflects accordingly.

Step 2: We use environment variables such as DATACOVES__AIRFLOW_DAGS_YML_PATH that are pre-configured for you. For more information on these variables see Datacoves Environment Variables - yml_path : This is where dbt-coves will look for the yml files to generate your Python DAGs. - dags_path : This is where dbt-coves will place your generated python DAGs.

Place the following in your config.yml file

    # source location for yml files
    yml_path: "/config/workspace/{{ env_var('DATACOVES__AIRFLOW_DAGS_YML_PATH') }}"

    # destination for generated python dags
    dags_path: "/config/workspace/{{ env_var('DATACOVES__AIRFLOW_DAGS_PATH') }}"


If using an Extract and Load tool in your DAG you can dynamically generate your sources; however, additional configuration will be needed inside the config.yml file. See Airbyte . For Fivetran contact us to complete the setup.

Create the yml file for your Airflow DAG

dbt-coves will look for your yml inside your orchestrate/dags_yml_definition folder to generate your Python DAGs. Please create these folders if you have not already done so.


When you create a DAG with YAML the name of the file will be the name of the DAG. eg) yml_dbt_dag.yml generates a dag named yml_dbt_dag

Let's create our first DAG using YAML.

Step 1 : Create a new file named my_first_yml.py in your orchestrate/dags folder.

Step 2: Add the following YAML to your file and be sure to change

description: "Sample DAG for dbt build"
schedule_interval: "0 0 1 */12 *"
  - version_2
  start_date: 2023-01-01
  owner: Noel Gomez # Replace this with your name
  email: gomezn@example.com # Replace with the email of the recipient for failures
  email_on_failure: true
catchup: false

    type: task
    operator: operators.datacoves.dbt.DatacovesDbtOperator
    bash_command: "dbt run -s personal_loans" 


In the examples we make use of the Datacoves Operators which handle things like copying and running dbt deps. For more information on what these operators handle, see Datacoves Operators

How to create your own task group with YAML

The example below shows how to create your own task group with YAML.

Field Reference:

  • type : This must be task_group
  • tooltip : Hover message for the task group.
  • tasks : Here is where you will define the individual tasks in the task group.


Specify the "task group" and "task" names at the beginning of their respective sections, as illustrated below:

  extract_and_load_dlt: # The name of the task group
    type: task_group
    tooltip: "dlt Extract and Load"

      load_us_population: # The name of the task 
        operator: operators.datacoves.bash.DatacovesBashOperator
        # activate_venv: true
        # Virtual Environment is automatically activated

        cwd: "load/dlt/csv_to_snowflake/"
        bash_command: "python load_csv_data.py"

      # Add more tasks here  

Generate your python file from your yml file

To generate your DAG, be sure you have the yml you wish to generate a DAG from open.

Select more in the bottom bar.

Select Generate Airflow Dag for YML . This will run the command to generate the individual yml.

Generate Airflow Dag

Generate all your python files

To generate all of the DAGs from your orchestrate/dag_yml_definitions/ directory

  • Run dbt-coves generate airflow-dags in your terminal.

All generated python DAGs will be placed in the orchestrate/dags

import datetime

from airflow.decorators import dag
from operators.datacoves.dbt import DatacovesDbtOperator

        "start_date": datetime.datetime(2023, 1, 1, 0, 0),
        "owner": "Noel Gomez",
        "email": "gomezn@example.com",
        "email_on_failure": True,
    description="Sample DAG for dbt build",
    schedule_interval="0 0 1 */12 *",
def yml_dbt_dag():
    run_dbt = DatacovesDbtOperator(
        task_id="run_dbt", bash_command="dbt run -s personal_loans"

dag = yml_dbt_dag()