Defining Celery tasks in Flask

Introduction

Celery tasks let your Flask app do work in the background. This helps keep your app fast and responsive.

Sending emails after a user signs up without making them wait

Processing uploaded files without blocking the user

Running scheduled jobs like cleaning up old data

Handling long calculations without freezing the app

Syntax

Flask

from celery import Celery

celery_app = Celery('myapp', broker='redis://localhost:6379/0')

@celery_app.task
def my_task(arg1, arg2):
    # task code here
    return arg1 + arg2

Use @celery_app.task to mark a function as a background task.

The broker is where Celery gets tasks from; Redis is a common choice.

Examples

A simple task that adds two numbers.

Flask

from celery import Celery

celery_app = Celery('app', broker='redis://localhost:6379/0')

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

A task that simulates sending an email.

Flask

from celery import Celery

celery_app = Celery('app', broker='redis://localhost:6379/0')

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

A task that retries itself on failure after 10 seconds.

Flask

from celery import Celery

celery_app = Celery('app', broker='redis://localhost:6379/0')

@celery_app.task(bind=True)
def retry_task(self):
    try:
        # risky code
        pass
    except Exception as e:
        self.retry(exc=e, countdown=10)

Sample Program

This program defines a Celery task to multiply two numbers. It sends the task to the queue and prints the task ID.

Flask

from celery import Celery

celery_app = Celery('flask_app', broker='redis://localhost:6379/0')

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

if __name__ == '__main__':
    result = multiply.delay(4, 5)
    print(f"Task sent. Task ID: {result.id}")

Important Notes

Remember to run a Celery worker separately to process tasks.

Use delay() to call tasks asynchronously.

Task IDs help track the status of background jobs.

Summary

Use @celery_app.task to define background tasks in Flask.

Tasks run outside the main app to keep it fast.

Call tasks with delay() to run them asynchronously.

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