Defining Celery tasks in Flask - Mini Project: Build & Apply

Defining Celery Tasks in Flask

📖 Scenario: You are building a Flask web application that needs to perform background tasks without blocking the main app. You will use Celery to define and run these tasks asynchronously.

🎯 Goal: Create a Celery task in a Flask app that adds two numbers and returns the result.

📋 What You'll Learn

Create a Celery instance linked to the Flask app

Define a simple Celery task function

Use the Celery task decorator correctly

Ensure the task can be called asynchronously

💡 Why This Matters

🌍 Real World

Background tasks like sending emails, processing images, or running long computations without blocking the web server.

💼 Career

Many web developer roles require knowledge of asynchronous task queues like Celery to build scalable and responsive applications.

1

Set up Flask app and Celery instance

Create a Flask app instance called app and a Celery instance called celery linked to app with the broker URL set to redis://localhost:6379/0.

Flask

from flask import Flask
from celery import Celery

# Your code here

Hint

Use Flask(__name__) to create the app and pass app.name and broker URL to Celery.

2

Configure Celery task decorator

Add a Celery task decorator to a function called add that takes two parameters x and y.

Flask

from flask import Flask
from celery import Celery

app = Flask(__name__)
celery = Celery(app.name, broker='redis://localhost:6379/0')

# Define the add task below
# Your code here

Hint

Use @celery.task above the function definition to make it a Celery task.

3

Call the Celery task asynchronously

Call the add task asynchronously using the delay method with arguments 4 and 6, and assign the result to a variable called result.

Flask

from flask import Flask
from celery import Celery

app = Flask(__name__)
celery = Celery(app.name, broker='redis://localhost:6379/0')

@celery.task
def add(x, y):
    return x + y

# Call the add task asynchronously
# Your code here

Hint

Use add.delay(4, 6) to call the task asynchronously and assign it to result.

4

Complete the Flask app with a route to trigger the task

Add a Flask route /start-task that triggers the add task asynchronously with 10 and 20, and returns a string with the task id using result.id.

Flask

from flask import Flask
from celery import Celery

app = Flask(__name__)
celery = Celery(app.name, broker='redis://localhost:6379/0')

@celery.task
def add(x, y):
    return x + y

result = add.delay(4, 6)

@app.route('/start-task')
def start_task():
    # Your code here

Hint

Use @app.route('/start-task') to define the route and call add.delay(10, 20) inside the function.

Practice

1. What is the main purpose of defining a Celery task in a Flask application using @celery_app.task?

easy

A. To make the Flask app run faster by disabling routes

B. To automatically restart the Flask server

C. To run functions asynchronously in the background

D. To create database models

Solution

1. Step 1: Understand Celery task decorator

   The @celery_app.task decorator marks a function to run as a background task outside the main Flask process.

2. Step 2: Purpose of asynchronous tasks

   This allows long-running or slow tasks to run without blocking the main app, improving responsiveness.

3. Final Answer:

   To run functions asynchronously in the background -> Option C

4. Quick Check:

   Celery tasks = background async functions [OK]

Hint: Celery tasks run outside Flask to avoid blocking [OK]

Common Mistakes:

• Thinking Celery tasks restart the server
• Confusing tasks with database models
• Believing tasks disable routes

2. Which of the following is the correct way to define a Celery task in Flask?

easy

A. @celery_app.task
def my_task(): pass

B. celery_app.run_task(my_task)

C. @app.route('/task')
def my_task(): pass

D. def my_task(): pass

Solution

1. Step 1: Identify the decorator for Celery tasks

   The correct decorator to define a Celery task is @celery_app.task.

2. Step 2: Check syntax correctness

   @celery_app.task def my_task(): pass correctly uses @celery_app.task above the function definition.

3. Final Answer:

   @celery_app.task\ndef my_task(): pass -> Option A

4. Quick Check:

   Use @celery_app.task to define tasks [OK]

Hint: Look for @celery_app.task decorator above function [OK]

Common Mistakes:

• Using Flask route decorator instead of Celery task
• Calling run_task instead of using decorator
• Defining function without decorator

3. Given the following code, what will be the output when add.delay(4, 5) is called?

from celery import Celery
celery_app = Celery('tasks')

@celery_app.task
def add(x, y):
    return x + y

result = add.delay(4, 5)
print(type(result))

medium

A. <class 'celery.result.AsyncResult'>

B. <class 'int'>

C. 9

D. None

Solution

1. Step 1: Understand what delay() returns

   The delay() method queues the task and returns an AsyncResult object, not the actual result.

2. Step 2: Check the printed type

   Printing type(result) shows the class of the returned object, which is celery.result.AsyncResult.

3. Final Answer:

   <class 'celery.result.AsyncResult'> -> Option A

4. Quick Check:

   delay() returns AsyncResult object [OK]

Hint: delay() returns AsyncResult, not the task output [OK]

Common Mistakes:

• Expecting delay() to return the task result immediately
• Confusing AsyncResult with the actual return value
• Printing result instead of type(result)

4. Identify the error in the following Celery task definition:

from celery import Celery
celery_app = Celery('tasks')

@celery_app.task()
def multiply(x, y):
    return x * y

result = multiply.delay(3, 7)
print(result.get())

medium

A. Using parentheses in @celery_app.task() decorator causes error

B. Calling delay() instead of apply_async() is wrong

C. Missing Flask app context inside the task

D. No error; code runs correctly

Solution

1. Step 1: Check decorator syntax

   Using parentheses in @celery_app.task() is allowed and works correctly.

2. Step 2: Verify delay() usage and result retrieval

   Calling delay() queues the task, and result.get() waits for and returns the result properly.

3. Final Answer:

   No error; code runs correctly -> Option D

4. Quick Check:

   Parentheses in decorator are optional and valid [OK]

Hint: Parentheses in @celery_app.task() are optional [OK]

Common Mistakes:

• Thinking parentheses cause syntax error
• Confusing delay() with apply_async()
• Assuming Flask context is always needed in tasks

5. You want to define a Celery task in Flask that sends emails but only if the recipient email is not empty. Which of the following task definitions correctly applies this condition inside the task?

hard

A. @celery_app.task
def send_email(email):
if email is not None:
print(f"Sending email to {email}")

B. @celery_app.task
def send_email(email):
if not email:
return
print(f"Sending email to {email}")

C. @celery_app.task
def send_email(email):
if email is None:
print("No email provided")
else:
print(f"Sending email to {email}")

D. @celery_app.task
def send_email(email):
print(f"Sending email to {email}")

Solution

1. Step 1: Understand the condition to skip empty emails

   The task should not send emails if the email is empty or falsy (like empty string).

2. Step 2: Check which option correctly skips empty emails

   @celery_app.task def send_email(email): if not email: return print(f"Sending email to {email}") uses if not email: return to exit early, preventing sending to empty emails.

3. Final Answer:

   if not email: return to skip empty emails -> Option B

4. Quick Check:

   Use if not email: return to skip empty input [OK]

Hint: Return early if email is empty to skip sending [OK]

Common Mistakes:

• Not checking for empty string, only None
• Sending email without any condition
• Using incorrect condition that doesn't skip empty