Unit testing DAGs in Apache Airflow - Practice Problems & Coding Challenges

Challenge - 5 Problems

💻 Command Output

intermediate

Output of a simple DAG test run

You have a DAG with one task that prints 'Hello Airflow'. You run a unit test that triggers this task. What will be the output of the test command?

Apache Airflow

def test_hello_task():
    ti = TaskInstance(task=hello_task, execution_date=datetime.now())
    ti.run()
    print(ti.xcom_pull())

A None

B TaskInstanceError

C SyntaxError

D Hello Airflow

💡 Hint

Think about what xcom_pull returns if no value is pushed.

The task prints 'Hello Airflow' but does not push any XCom value, so ti.xcom_pull() returns None.

🧠 Conceptual

intermediate

Purpose of mocking in DAG unit tests

Why do we use mocking when unit testing Airflow DAGs?

A To deploy DAGs automatically

B To simulate external systems and isolate the DAG logic

C To speed up the Airflow scheduler

D To generate DAG documentation

💡 Hint

Think about how to test code without relying on real external services.

Mocking replaces external dependencies with fake ones so tests focus only on DAG logic.

❓ Troubleshoot

advanced

Diagnosing a failing DAG unit test

A unit test for a DAG task fails with the error: 'TaskInstanceStateError: Task instance is in state None'. What is the most likely cause?

A The task was not properly initialized with an execution date

B The DAG file has syntax errors

C The Airflow webserver is down

D The task has no downstream dependencies

💡 Hint

Check how TaskInstance is created in tests.

TaskInstance requires a valid execution_date to track state; missing it causes this error.

✅ Best Practice

advanced

Best practice for testing task dependencies in DAGs

Which approach best verifies task dependencies in an Airflow DAG unit test?

A Manually inspect the DAG Python file

B Run all tasks and check their logs

C Use Airflow CLI to list all DAGs

D Check the DAG's task dictionary for upstream and downstream task IDs

💡 Hint

Think about programmatic ways to verify dependencies.

Accessing task attributes programmatically allows automated verification of dependencies.

🔀 Workflow

expert

Correct order of steps in unit testing an Airflow DAG

Arrange the following steps in the correct order for unit testing an Airflow DAG:

A 3,1,2,4

B 1,3,2,4

C 1,2,3,4

D 2,1,3,4

💡 Hint

Think about preparing the environment before running tests.

First import DAG/tasks, then mock dependencies, create TaskInstances, then run and assert.