Task documentation and tags in Apache Airflow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a description to an Airflow task.

Apache Airflow

task = PythonOperator(task_id='print_date', python_callable=print_date, dag=dag, [1]='Prints the current date')

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

Atags

Bdescription

Cdoc_md

Downer

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'description' instead of 'doc_md'

Confusing 'tags' with documentation

The doc_md parameter is used to add documentation to an Airflow task in markdown format.

2fill in blank

medium

Complete the code to add tags to an Airflow task.

Apache Airflow

task = BashOperator(task_id='run_script', bash_command='echo Hello', dag=dag, [1]=['example', 'test'])

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

Atags

Bdoc_md

Cowner

Ddescription

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'doc_md' instead of 'tags'

Trying to assign tags with 'description'

The tags parameter is used to assign tags to an Airflow task for easier filtering and organization.

3fill in blank

hard

Fix the error in the task definition to correctly add documentation.

Apache Airflow

task = PythonOperator(task_id='task1', python_callable=my_func, dag=dag, doc_md=[1])

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

AThis is a task documentation

B'This is a task documentation'

C['This is a task documentation']

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Not using quotes around the string

Passing a list instead of a string

The doc_md parameter expects a string with markdown content, so it must be enclosed in quotes.

4fill in blank

hard

Fill both blanks to add tags and documentation to an Airflow task.

Apache Airflow

task = BashOperator(task_id='task2', bash_command='ls', dag=dag, [1]=['data', 'etl'], [2]='Lists files in directory')

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

Atags

Bdoc_md

Cowner

Ddescription

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping tags and doc_md

Using description instead of doc_md

tags is used to assign tags, and doc_md is used for task documentation.

5fill in blank

hard

Fill all three blanks to add tags, documentation, and owner to an Airflow task.

Apache Airflow

task = PythonOperator(task_id='task3', python_callable=my_func, dag=dag, [1]=['analytics'], [2]='Runs analytics job', [3]='data_team')

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

Atags

Bdoc_md

Cowner

Ddescription

Attempts:

3 left

💡 Hint

Common Mistakes

Using description instead of doc_md

Mixing up owner and tags

tags assigns tags, doc_md adds documentation, and owner specifies the task owner.

Practice

1. What is the main purpose of adding documentation to an Airflow task using doc_md?

easy

A. To explain what the task does for better understanding

B. To change the task execution order

C. To assign tags for task grouping

D. To increase task execution speed

Solution

1. Step 1: Understand the role of doc_md in Airflow

   doc_md is used to add markdown documentation to a task, explaining its purpose and behavior.

2. Step 2: Differentiate documentation from other features

   Documentation does not affect execution order, tags, or speed; it only improves clarity.

3. Final Answer:

   To explain what the task does for better understanding -> Option A

4. Quick Check:

   Task documentation = Explanation [OK]

Hint: Documentation explains task purpose, not execution or tags [OK]

Common Mistakes:

• Confusing documentation with tags
• Thinking documentation changes task order
• Assuming documentation affects performance

2. Which of the following is the correct way to add tags to an Airflow task in Python code?

easy

A. task = PythonOperator(task_id='task1', python_callable=my_func, tag='tag1')

B. task = PythonOperator(task_id='task1', python_callable=my_func, tags=['tag1', 'tag2'])

C. task = PythonOperator(task_id='task1', python_callable=my_func, tags='tag1,tag2')

D. task = PythonOperator(task_id='task1', python_callable=my_func, labels=['tag1', 'tag2'])

Solution

1. Step 1: Recall the correct parameter for tags

   Airflow tasks accept a tags parameter as a list of strings to assign multiple tags.

2. Step 2: Check syntax correctness

   task = PythonOperator(task_id='task1', python_callable=my_func, tags=['tag1', 'tag2']) uses tags=['tag1', 'tag2'] which is the correct syntax. Other options use incorrect parameter names or types.

3. Final Answer:

   task = PythonOperator(task_id='task1', python_callable=my_func, tags=['tag1', 'tag2']) -> Option B

4. Quick Check:

   Tags parameter = list of strings [OK]

Hint: Use tags as a list with key 'tags' in operator [OK]

Common Mistakes:

• Using 'tag' instead of 'tags'
• Passing tags as a comma string
• Using 'labels' instead of 'tags'

3. Given this Airflow task code snippet, what will be the value of task.doc_md?

task = PythonOperator(
    task_id='example_task',
    python_callable=lambda: print('Hello'),
    doc_md="""This task prints a greeting message."""
)

medium

A. None

B. "Prints a message"

C. SyntaxError

D. "This task prints a greeting message."

Solution

1. Step 1: Identify the doc_md assignment

   The task is created with doc_md set to a triple-quoted string describing the task.

2. Step 2: Understand doc_md stores the documentation string

   The doc_md attribute holds the exact string provided, so it will be "This task prints a greeting message.".

3. Final Answer:

   "This task prints a greeting message." -> Option D

4. Quick Check:

   doc_md value = given string [OK]

Hint: doc_md stores the exact documentation string given [OK]

Common Mistakes:

• Assuming doc_md is None if not printed
• Confusing doc_md with task output
• Expecting syntax error from triple quotes

4. You wrote this Airflow task but it fails to assign tags properly:

task = PythonOperator(
    task_id='task_fail',
    python_callable=my_func,
    tag=['data', 'etl']
)

What is the error and how to fix it?

medium

A. Parameter should be 'tags' not 'tag'; fix by changing to tags=['data', 'etl']

B. PythonOperator does not support tags; remove the tag parameter

C. Tags must be a string, not a list; fix by tags='data,etl'

D. The task_id is invalid; change task_id to 'task_fail_1'

Solution

1. Step 1: Identify the incorrect parameter name

   The code uses tag instead of the correct tags parameter for assigning tags.

2. Step 2: Correct the parameter name and keep the list format

   Changing tag=['data', 'etl'] to tags=['data', 'etl'] fixes the issue.

3. Final Answer:

   Parameter should be 'tags' not 'tag'; fix by changing to tags=['data', 'etl'] -> Option A

4. Quick Check:

   Correct parameter name = tags [OK]

Hint: Use 'tags' plural, not 'tag' singular [OK]

Common Mistakes:

• Using 'tag' instead of 'tags'
• Passing tags as a string instead of list
• Blaming task_id for tag issues

5. You want to organize your Airflow DAG tasks by adding documentation and tags. Which code snippet correctly adds both a markdown description and multiple tags to a task?

hard

A. task = PythonOperator(task_id='task1', python_callable=my_func, doc_md=['Runs ETL process'], tags='etl,daily')

B. task = PythonOperator(task_id='task1', python_callable=my_func, documentation='Runs ETL process', tag=['etl', 'daily'])

C. task = PythonOperator(task_id='task1', python_callable=my_func, doc_md='Runs ETL process', tags=['etl', 'daily'])

D. task = PythonOperator(task_id='task1', python_callable=my_func, doc_md='Runs ETL process', labels=['etl', 'daily'])

Solution

1. Step 1: Verify correct parameter names and types

   doc_md should be a string with markdown text, and tags should be a list of strings.

2. Step 2: Check each option for correctness

   task = PythonOperator(task_id='task1', python_callable=my_func, doc_md='Runs ETL process', tags=['etl', 'daily']) uses doc_md='Runs ETL process' (string) and tags=['etl', 'daily'] (list), which is correct. Others use wrong parameter names or types.

3. Final Answer:

   task = PythonOperator(task_id='task1', python_callable=my_func, doc_md='Runs ETL process', tags=['etl', 'daily']) -> Option C

4. Quick Check:

   doc_md = string, tags = list [OK]

Hint: Use doc_md as string and tags as list for both features [OK]

Common Mistakes:

• Using 'documentation' instead of 'doc_md'
• Passing tags as string instead of list
• Using 'labels' instead of 'tags'