XCom with return values in Apache Airflow - Mini Project: Build & Apply

XCom with return values

📖 Scenario: You are working with Apache Airflow to automate tasks. You want to pass data between tasks using XComs, which allow tasks to share small pieces of information.Imagine you have two tasks: one that generates a number, and another that uses that number to print a message.

🎯 Goal: Build a simple Airflow DAG with two Python tasks. The first task returns a value using XCom. The second task reads that value and prints it.

📋 What You'll Learn

Create a Python function called generate_number that returns the integer 42.

Create a Python function called print_number that accepts ti as a parameter and pulls the XCom value from generate_number task.

Create a DAG named xcom_return_value_dag with two tasks: task_generate and task_print.

Set task_generate to run generate_number and task_print to run print_number.

Set task_generate to run before task_print.

Print the pulled XCom value inside print_number.

💡 Why This Matters

🌍 Real World

In real Airflow workflows, tasks often need to share data like IDs, statuses, or results. XComs let you pass this data easily between tasks.

💼 Career

Understanding XComs is essential for Airflow users and DevOps engineers who automate workflows and need tasks to communicate with each other.

1

Create the generate_number function

Write a Python function called generate_number that returns the integer 42.

Apache Airflow

# Your code here

Hint

Define a function with def and use return 42 inside it.

2

Create the print_number function to pull XCom

Write a Python function called print_number that accepts a parameter ti. Inside it, pull the XCom value from the task task_generate using ti.xcom_pull(task_ids='task_generate') and store it in a variable called number.

Apache Airflow

def generate_number():
    return 42

# Your code here

Hint

Use ti.xcom_pull(task_ids='task_generate') to get the value returned by generate_number.

3

Create the DAG and tasks

Import DAG and PythonOperator from Airflow. Create a DAG named xcom_return_value_dag with start_date as days_ago(1) and schedule_interval as None. Inside the DAG, create two tasks: task_generate running generate_number and task_print running print_number. Set task_generate to run before task_print.

Apache Airflow

def generate_number():
    return 42

def print_number(ti):
    number = ti.xcom_pull(task_ids='task_generate')

# Your code here

Hint

Use PythonOperator to run your functions as tasks inside the DAG context.

4

Print the pulled XCom value in print_number

Add a print statement inside the print_number function to display the variable number.

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.utils.dates import days_ago

def generate_number():
    return 42

def print_number(ti):
    number = ti.xcom_pull(task_ids='task_generate')
    # Your code here

with DAG(
    'xcom_return_value_dag',
    start_date=days_ago(1),
    schedule_interval=None
) as dag:
    task_generate = PythonOperator(
        task_id='task_generate',
        python_callable=generate_number
    )

    task_print = PythonOperator(
        task_id='task_print',
        python_callable=print_number
    )

    task_generate >> task_print

Hint

Use print(number) to show the value pulled from XCom.

Practice

1. What does returning a value from a PythonOperator task do in Airflow?

easy

A. Automatically pushes the returned value to XCom for other tasks to use.

B. Saves the value only in the task logs without sharing.

C. Deletes any previous XCom values for that task.

D. Triggers the next task immediately without waiting.

Solution

1. Step 1: Understand PythonOperator return behavior

   When a PythonOperator returns a value, Airflow automatically stores it in XCom for that task instance.

2. Step 2: Recognize XCom purpose

   XCom is designed to share data between tasks, so returning a value pushes it to XCom for downstream tasks.

3. Final Answer:

   Automatically pushes the returned value to XCom for other tasks to use. -> Option A

4. Quick Check:

   Return value = XCom push [OK]

Hint: Return values from PythonOperator go to XCom automatically [OK]

Common Mistakes:

• Thinking return values are only logged, not shared
• Assuming return clears previous XCom data
• Believing return triggers next task immediately

2. Which of the following is the correct way to pull an XCom value in a downstream task?

easy

A. ti.xcom_pull(task_ids='task1', key='return_value')

B. ti.xcom_push(key='result')

C. xcom_pull(task_id='task1')

D. ti.pull_xcom(task_id='task1')

Solution

1. Step 1: Identify correct method signature

   The method to pull XCom data is ti.xcom_pull(), which requires task_ids and optionally a key.

2. Step 2: Match correct parameters

   Correct usage is ti.xcom_pull(task_ids='task1', key='return_value') to get the returned value from task1.

3. Final Answer:

   ti.xcom_pull(task_ids='task1', key='return_value') -> Option A

4. Quick Check:

   Use ti.xcom_pull with task_ids and key [OK]

Hint: Use ti.xcom_pull(task_ids, key) to get XCom data [OK]

Common Mistakes:

• Using xcom_push instead of xcom_pull to get data
• Wrong parameter names like task_id instead of task_ids
• Calling non-existent methods like ti.pull_xcom

3. Given this DAG snippet:

def task1():
    return {'value': 42}

def task2(ti):
    data = ti.xcom_pull(task_ids='task1')
    print(data)

What will task2 print when executed?

medium

A. None

B. {'return_value': {'value': 42}}

C. 42

D. Error: xcom_pull missing key

Solution

1. Step 1: Understand task1 return value

   task1 returns a dictionary {'value': 42}, which is pushed to XCom automatically.

2. Step 2: Analyze task2 xcom_pull call

   task2 calls ti.xcom_pull(task_ids='task1') without a key, so it pulls all XCom values from task1 as a dictionary {'return_value': {'value': 42}}.

3. Final Answer:

   {'return_value': {'value': 42}} -> Option B

4. Quick Check:

   Pull without key returns XComs dict [OK]

Hint: Pull without key returns XComs dict [OK]

Common Mistakes:

• Expecting only the inner value without specifying key
• Assuming None if key is not given
• Thinking it raises an error without key

4. What is wrong with this code snippet?

def task1():
    return 100

def task2(ti):
    value = ti.xcom_pull(task_ids='task1', key='value')
    print(value)

medium

A. task2 must use task_id instead of task_ids in xcom_pull.

B. task1 should push to XCom manually using xcom_push.

C. task2 pulls with wrong key; default return key is 'return_value'.

D. task1 return value must be a string, not int.

Solution

1. Step 1: Check task1 return and XCom key

   task1 returns 100, which is stored in XCom with the default key 'return_value'.

2. Step 2: Analyze task2 xcom_pull key usage

   task2 tries to pull with key='value', which does not exist, so it will return None.

3. Final Answer:

   task2 pulls with wrong key; default return key is 'return_value'. -> Option C

4. Quick Check:

   Default XCom key for return is 'return_value' [OK]

Hint: Default XCom key for return is 'return_value' [OK]

Common Mistakes:

• Thinking return requires manual xcom_push
• Using wrong key name in xcom_pull
• Confusing task_id and task_ids parameter names

5. You want to pass a dictionary from task1 to task3 through task2 without modifying task2. Which is the best way to do this using XCom return values?

hard

A. Use Airflow Variables instead of XCom for this data passing.

B. Have task1 push manually; task2 returns the same dictionary to pass it on.

C. Modify task2 to pull from task1 and push to task3 manually.

D. Have task1 return the dictionary; task3 pulls it directly using ti.xcom_pull(task_ids='task1').

Solution

1. Step 1: Understand XCom chaining

   XCom stores data per task instance; tasks can pull data from any previous task by specifying task_ids.

2. Step 2: Avoid modifying task2

   Since task2 should not be changed, task3 can pull data directly from task1's XCom return value.

3. Final Answer:

   Have task1 return the dictionary; task3 pulls it directly using ti.xcom_pull(task_ids='task1'). -> Option D

4. Quick Check:

   Pull directly from original task to avoid modifying intermediates [OK]

Hint: Pull XCom directly from original task to skip intermediate tasks [OK]

Common Mistakes:

• Thinking data must pass through every intermediate task
• Modifying tasks unnecessarily to forward XCom
• Using Variables instead of XCom for task-to-task data