How to Validate Airflow DAGs With an Import Test in CI

Loading every DAG through DagBag surfaces import errors that only appear when the scheduler parses the file.

Run a pytest that builds a DagBag from your dags folder and asserts import_errors is empty, catching parse failures before deploy.

Steps

• Install apache-airflow matching your production version.
• Point AIRFLOW__CORE__DAGS_FOLDER at your dags directory.
• Assert DagBag().import_errors is empty in a test.
• Run the test on every pull request.

Test

from airflow.models import DagBag

def test_no_import_errors():
    dag_bag = DagBag(dag_folder="dags", include_examples=False)
    assert dag_bag.import_errors == {}, dag_bag.import_errors

def test_dags_have_owner_and_tags():
    dag_bag = DagBag(dag_folder="dags", include_examples=False)
    for dag_id, dag in dag_bag.dags.items():
        assert dag.tags, f"{dag_id} is missing tags"

Workflow

on: [pull_request]
jobs:
  dags:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.11'
      - run: pip install "apache-airflow==2.9.3" pytest
      - run: pytest tests/test_dag_validation.py -q

Gotchas

• Pin the Airflow version to match production so provider imports resolve the same way.
• A slow DAG top-level (network calls at parse time) will slow every scheduler loop; catch it here.

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