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)
