Flask provides a flexible and efficient platform for job scheduling in web applications. With libraries like APScheduler, cron jobs, and extensions like Redwood, developers can automate tasks, manage scheduled jobs, and improve the efficiency of their Flask applications. 

Whether it’s executing tasks at regular intervals, using cron syntax for specific schedules, or leveraging powerful extensions, Flask offers a range of options to suit various job scheduling needs. By combining the simplicity and power of Flask with the versatility of Python, users can create robust and efficient web apps with automated job scheduling capabilities.

What is Flask? 

Flask is a micro web framework written in Python that allows developers to build web applications quickly and easily. It’s designed to be lightweight, flexible, and easy to understand, so it’s great for developing web applications of varying complexities.

Flask provides tools and libraries to create web APIs, handle routing, manage databases, and more. It can also be used to create RESTful APIs and microservices for deployment on a variety of platforms, including cloud-based tools like AWS. 

What is a Flask app? 

A Flask app is a Python module that contains the web application’s logic and routes. It serves as the entry point for the web application and provides the necessary configuration and functionality. 

With Flask, developers can define routes, handle requests, and render HTML templates. Additionally, Flask supports extensions and plugins so devs can enhance their web app with additional features like authentication, database integration, and job scheduling.

Flask API 

Flask provides a simple and intuitive API for building web applications. Developers can define routes using decorators and specify the functions that handle those routes.

For example, the following Python code snippet demonstrates a basic Flask application that displays “Hello, World!” when accessing the root URL:

from flask import Flask

app = Flask(__name__)


def hello_world():

    return 'Hello, World!'

if __name__ == '__main__':


In the above example, the @app.route(‘/’) decorator specifies that the following function should handle requests to the root URL (“/”). The hello_world() function is executed when a user accesses the root URL, and returns the string “Hello, World!” as the response. Flask takes care of handling the HTTP request and response so devs can focus on the web app’s logic.

Flask & Python: Understanding the Connection   

Flask is built on top of Python and can thus take advantage of its powerful features and libraries. It leverages the simplicity and readability of Python code for easy development of web applications. Python provides a vast ecosystem of libraries and modules that can be integrated into Flask web apps to extend functionality and enable job scheduling.

In regards to job scheduling specifically, Python’s datetime module can be used to handle date and time calculations, which is essential for scheduled jobs. And libraries like APScheduler and Celery can be integrated with Flask to facilitate scheduled tasks.

Scheduled Jobs with Flask: APScheduler 

APScheduler is a popular Python library that provides a job scheduling mechanism for applications. It can be seamlessly integrated with Flask to automate tasks and execute them at predefined intervals. To use APScheduler with Flask, follow this tutorial using Python code:

1. Install the Flask-APScheduler extension from the Python Package Index (PyPi) using pip:

pip install Flask-APScheduler

2. Import the necessary modules to create a Flask app: 

from flask import Flask

from flask_apscheduler import APScheduler

app = Flask(__name__)

scheduler = APScheduler()

3. Configure the Flask app and scheduler.

if __name__ == '__main__':




4. Define and schedule a job function:

@scheduler.task('interval', id='my_job', seconds=10)

def my_job():

    print('This job is executed every 10 seconds.')

The id parameter ensures that only one instance of the job is running at a time, and the seconds parameter defines the interval between executions.

The Flask-APScheduler includes a REST API for managing scheduled jobs. Users can access docs for Flask APScheduler on GitHub.  

Scheduled Jobs with Flask: Cron Jobs 

Cron jobs are another popular method for scheduling recurring tasks in web applications. Flask allows users to leverage cron jobs through various libraries and tools, including the crontab module.

To use cron jobs with Flask, take the following steps outlined in the below tutorial using Python code:

Install necessary dependencies, including the crontab module:

pip install python-crontab

Import required modules and define the Flask app:

from flask import Flask
from crontab import CronTab

app = Flask(__name__)
cron = CronTab(user='your_username')

Replace ‘your_username’ in the above example with the actual username and config the Flask app and cron job.

if __name__ == '__main__':

Define a job function and schedule it with cron syntax:

job = cron.new(command='python /path/to/your_script.py')

The command parameter above specifies the command to be executed. Replace /path/to/your_script.py with the actual path to the Python script.

Next, set the schedule using cron syntax using the following command:

job.setall('*/5 * * * *')  

This example runs the job every 5 minutes.


Save the cron job.

Redwood Flask Job Scheduler 

Redwood offers event-driven job scheduling software for enterprise teams. Jobs and IT processes can be easily scheduled with RedWood RunMyJobs. By supporting more than 25 scripting languages, including Python with built-in syntax highlighting and parameter replacement, Redwood offers seamless job scheduling with Flask.

Offering the ability to automate job scheduling on any platform, Redwood controls servers and runs scripts with lightweight agents for Windows, Linux, AIX, macOS, and more. The tool has an intuitive, low-code UI with a drag-and-drop graphical editor. An extensive library of templates and wizards enables teams to create new jobs in minutes.

Enterprise teams can automate endless use cases with Redwood RunMyJobs including IT operations, managed file transfer, and business processes. Orchestrate securely and reliably across applications, services, and servers in the cloud or on-prem within a single platform. Redwood helps guarantee high performance of business applications with predictive SLA monitoring and notifications through email and SMS.

Job Scheduling with Flask Frequently Asked Questions

How do I automatically run a Flask app?

To automatically run a Flask app, create an __init__.py file in the project's root directory and define the Flask app inside it. This file will be automatically executed when the project is launched. Alternatively, use a WSGI server, such as Gunicorn or uWSGI, to deploy a Flask app on a production server. They can also be deployed as Docker containers.

Learn how teams can simply SAP job scheduling integration with Redwood.

What are some alternatives to Flask?

Flask is just one of the many web frameworks available in Python. Some alternatives include Django, Pyramid, Bottle, and Tornado. Each framework has its own strengths and focuses on different aspects of web development.

Redwood RunMyJobs can be used with Python and as an alternative to Flask for job scheduling.

Can I use Flask with Celery?

Celery is a distributed task queue system that can be integrated with Flask to handle asynchronous task processing. Flask-Celery is a Flask extension that simplifies the integration process.

This extension provides a convenient way to define and execute tasks asynchronously within a Flask application. By combining Flask and Celery, users offload time-consuming tasks to the backend, improving overall performance and responsiveness of the application.

Here is a Python code tutorial for using Flask with Celery:

from flask import Flask
from celery import Celery

Create a Flask app.

app = Flask(__name__)

Configure Celery.

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

Configure Celery to use Flask's app context.


Define a Celery task.

def add_numbers(x, y):
    return x + y

Define a Flask route.


Call the Celery task.

def home():
    result = add_numbers.delay(5, 10)
    return f'Task ID: {result.task_id}'

if __name__ == '__main__':

Easily manage cross-platform scheduling and batch jobs with Redwood RunMyJobs.