from airflow.models import DAG
from airflow.utils.dates import days_ago, timedelta

from fansifter.callbacks.slack import on_dag_failure_slack_callback
from fansifter.operators.runtime_estimation import RuntimeEstimationModelTrainingOperator

default_dag_args = dict(start_date=days_ago(1), owner="fansifter")
with DAG(
    dag_id="runtime_estimation_training_dag",
    schedule_interval=timedelta(hours=6),
    default_args=default_dag_args,
    catchup=False,
    on_failure_callback=on_dag_failure_slack_callback,
) as dag:
    models_training = RuntimeEstimationModelTrainingOperator(task_id="TrainModels")