Dynamic task generation with loops in Apache Airflow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a dynamic task inside the DAG using a loop.

Apache Airflow

for i in range(3):
    task = PythonOperator(task_id=f'task_[1]', python_callable=my_function, dag=dag)

Drag options to blanks, or click blank then click option'

Ai

Bindex

Ctask

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable name not defined in the loop like 'index' or 'count'.

Forgetting to use the loop variable to create unique task IDs.

The variable i is used in the loop to generate unique task IDs dynamically.

2fill in blank

medium

Complete the code to add tasks to the DAG dynamically using a loop and list comprehension.

Apache Airflow

tasks = [PythonOperator(task_id=f'task_[1]', python_callable=my_function, dag=dag) for [1] in range(5)]

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Acount

Btask

Cindex

Di

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable name not defined in the comprehension like 'task' or 'count'.

Not matching the loop variable in both places.

The loop variable i is used inside the list comprehension to create multiple tasks with unique IDs.

3fill in blank

hard

Fix the error in the dynamic task creation loop by completing the missing part.

Apache Airflow

for i in range(3):
    task = PythonOperator(task_id=f'task_[1]', python_callable=my_function, dag=dag)
    task.set_downstream(next_task)

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Atask

Bi

Cnext_task

Dindex

Attempts:

3 left

💡 Hint

Common Mistakes

Using a fixed string for task_id causing duplicate task IDs.

Using an undefined variable in the f-string.

The loop variable i must be used to create unique task IDs to avoid task ID conflicts.

4fill in blank

hard

Fill both blanks to create tasks dynamically and set dependencies between them.

Apache Airflow

tasks = []
for [1] in range(3):
    task = PythonOperator(task_id=f'task_[1]', python_callable=my_function, dag=dag)
    tasks.append(task)
for i in range(2):
    tasks[i].[2](tasks[i+1])

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Ai

Bset_upstream

Cset_downstream

Dappend

Attempts:

3 left

💡 Hint

Common Mistakes

Using set_upstream instead of set_downstream for dependencies.

Not using the loop variable for unique task IDs.

The loop variable i is used to create unique task IDs and set_downstream sets the order of task execution.

5fill in blank

hard

Fill all three blanks to create a dictionary of tasks dynamically with conditions.

Apache Airflow

tasks = {f'task_[1]': PythonOperator(task_id=f'task_[1]', python_callable=my_function, dag=dag) for [2] in range(5) if [3] % 2 == 0}

Drag options to blanks, or click blank then click option'

Ai

Bj

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variables inconsistently.

Not applying the modulo condition correctly.

The variable i is used for task IDs and loop iteration, and the condition filters even numbers.