def test_dag_import(): """Test that the DAG file can be successfully imported. This tests that the DAG can be parsed, but does not run it in an Airflow environment. This is a recommended confidence check by the official Airflow docs: https://airflow.incubator.apache.org/tutorial.html#testing """ from . import simple as module internal_unit_testing.assert_has_valid_dag(module)
def test_dag_with_variables(set_variables): # Importing the module verifies that there are no syntax errors. from . import unit_testing_variables as module # The assert_has_valid_dag verifies that the module contains an Airflow DAG # and that the DAG contains no cycles. internal_unit_testing.assert_has_valid_dag(module)
def test_dag_import(): """Test that the DAG file can be successfully imported. This tests that the DAG can be parsed, but does not run it in an Airflow environment. This is a recommended confidence check by the official Airflow docs: https://airflow.incubator.apache.org/tutorial.html#testing """ models.Variable.set("project_id", "example-project") from . import dataproc_workflow_template_instantiate_operator_tutorial as module internal_unit_testing.assert_has_valid_dag(module)
def test_dag_import(): """Test that the DAG file can be successfully imported. This tests that the DAG can be parsed, but does not run it in an Airflow environment. This is a recommended confidence check by the official Airflow docs: https://airflow.incubator.apache.org/tutorial.html#testing """ models.Variable.set('gcs_bucket', 'example_bucket') models.Variable.set('gcp_project', 'example-project') models.Variable.set('gce_zone', 'us-central1-f') from . import hadoop_tutorial as module internal_unit_testing.assert_has_valid_dag(module)
def test_dag_with_variables(): from airflow import models # Set any Airflow variables before importing the DAG module. models.Variable.set('gcp_project', 'example-project') # Importing the module verifies that there are no syntax errors. from . import unit_testing_variables as module # The assert_has_valid_dag verifies that the module contains an Airflow DAG # and that the DAG contains no cycles. internal_unit_testing.assert_has_valid_dag(module)
def test_dag_import(): """Test that the DAG file can be successfully imported. This tests that the DAG can be parsed, but does not run it in an Airflow environment. This is a recommended confidence check by the official Airflow docs: https://airflow.incubator.apache.org/tutorial.html#testing """ models.Variable.set("bucket_path", "gs://example_bucket") models.Variable.set("project_id", "example-project") models.Variable.set("gce_zone", "us-central1-f") models.Variable.set("gce_region", "us-central1-f") from . import dataflowtemplateoperator_tutorial as module internal_unit_testing.assert_has_valid_dag(module)
def test_dag_import(): from . import example_dag internal_unit_testing.assert_has_valid_dag(example_dag)
def test_dag_has_cycle(): from . import unit_testing_cycle as module with pytest.raises(exceptions.AirflowDagCycleException): internal_unit_testing.assert_has_valid_dag(module)
def test_dag_no_dag(): import internal_unit_testing as module # Does not contain a DAG. with pytest.raises(AssertionError): internal_unit_testing.assert_has_valid_dag(module)
def test_dag_import(): from . import data_orchestration_blog_sample_dag internal_unit_testing.assert_has_valid_dag( data_orchestration_blog_sample_dag)
def test_dag_import(): models.Variable.set('gcp_project', PROJECT_ID) from . import example_dag internal_unit_testing.assert_has_valid_dag(example_dag)