Django Celery Mastery: Python Asynchronous Task Processing

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1. Source Code

1. Introduction.mp4

00:41

2.1 Section-3-Final.zip

2.2 Section-4-Final(Not including the last tutorial).zip

2.3 Section-5-Final.zip

2.4 Section-6-Final.zip

2. Code Examples.html

2. Setup Guides

1. [Windows] Installing Python.mp4

05:34

2. [Windows] Visual Studio Code Induction.mp4

07:18

3. [Windows] Creating Virtual Environments.mp4

09:23

4. [macOS] Visual Studio Code Induction.mp4

07:55

5. [macOS] Installing Python.mp4

05:49

6. [macOS] Creating Virtual Environments.mp4

04:56

7. Docker Installation.html

3. Preparing a Django Celery Working Environment

1. Introducing Django Celery.mp4

10:21

2. Introducing Task Producers.mp4

02:28

3. Building a Django Docker Container.mp4

33:54

4. Building a Redis Docker Container.mp4

01:34

5. Introducing Task consumers (Workers).mp4

03:35

6. Building a Celery Worker Docker Container.mp4

03:02

7.1 1.7.zip

7. Introducing Results Backend.mp4

07:49

4. Defining and Executing Celery Tasks

1. Creating and Registering Celery Tasks in Django.mp4

12:57

2. Starting the Celery Worker.mp4

04:09

3.1 2.3.zip

3. Initiating a Celery Task.mp4

10:50

4.1 2.4.zip

4. Creating a new standalone Celery Worker.mp4

17:36

5. Introducing Tasks Routing.mp4

06:00

6. Configuring Task Routing.mp4

11:35

7. Introducing Celery Task Prioritization.mp4

03:01

8.1 2.8.zip

8. Configuring Task Prioritization (Redis).mp4

10:56

9. The Primitives - Task Grouping.mp4

04:37

10. The Primitives - Task Chaining.mp4

04:24

11.1 2.11.zip

11. Task Rate limits.mp4

05:28

12.1 2.12.zip

12. Configuring Task Prioritization (RabbitMQ).mp4

21:45

13.1 2.13.zip

13. Passing arguments and returning results from Celery tasks.mp4

09:33

14.1 2.14.zip

14. Executing tasks synchronously and asynchronously.mp4

07:52

15. Monitoring Celery Workers and Tasks with Flower.mp4

11:09

5. Handling Task Failures and Retries

1. Common Types of Exceptions and Errors in Celery Tasks.mp4

04:41

2. Dynamic Task Discovery in Celery Auto-discovering Tasks in a Directory.mp4

16:14

3. Error Handling Try Except Blocks.mp4

14:27

4. Handling Errors in Celery Tasks with Custom Task Classes.mp4

12:16

5. Implementing Automatic Retries.mp4

07:35

6. Error Handling in Groups.mp4

13:29

7. Towards Error Handling in Task Chains.mp4

06:35

8. Towards Dead-letter Queues Handling Failed Tasks.mp4

17:42

9. Task Timeouts and Task Revoking (Using task time limits and timeouts).mp4

17:09

10. Handling Errors in Task Result Callbacks.mp4

09:18

11. Task Signals Graceful Shutdown and Cleanup of Failed Tasks.mp4

09:10

12.1 3.12.zip

12. Error Tracking and Monitoring with Sentry.mp4

12:07

6. Task Scheduling and Periodic Tasks

1. Introduction to Task Scheduling.mp4

06:10

2. Scheduling Tasks to Run at Specific Times or Intervals.mp4

10:28

3. Implementing Periodic Tasks Customization.mp4

05:18

4. Crontab Schedules.mp4

05:25

5.1 4.5.zip

5. Implement Schedule Persistence for Celery in a Django Application.mp4

14:00

6. Schedule a Django Custom Command with Celery Beat.mp4

14:51

7.1 4.7.zip

7. Monitoring Service Status Including Custom Event Tracking and Alerting.mp4

25:26

Description

Unlocking the Power of Asynchronous Task Processing with Python Celery

What You'll Learn?

Module 1: You will learn how to set up a working environment for Django Celery by building Docker containers for Django, Redis, and Celery workers.
Module 2: You will learn to create and register tasks within a Django application, start and manage Celery.
Module 3: You will learn to identify common exceptions and errors in Celery tasks and implement error control.
Module 4: You will learn to schedule tasks at specific times or intervals, customize periodic tasks, and utilize crontab schedules.
By the end of the course, you will have a solid understanding of Django Celery and be equipped to leverage its power.

Who is this for?

Python Developers: Developers who are already familiar with the Python programming language and want to expand their knowledge and skills in asynchronous task processing using Django Celery.

Django Developers: Developers who are experienced in Django web development and want to incorporate asynchronous task processing into their Django applications to enhance performance and scalability.

Web Application Developers: Professionals involved in web application development who want to learn how to leverage Django Celery for handling time-consuming and resource-intensive tasks asynchronously, such as sending emails, generating reports, or processing large datasets.

Software Engineers: Software engineers interested in learning about task queues and asynchronous processing in Python and Django.

Backend Developers: Backend developers who want to improve the efficiency of their applications by offloading time-consuming tasks to background workers using Django Celery.

Technical Leads and Architects: Technical leads and architects responsible for designing and implementing scalable and performant systems who want to explore asynchronous task processing techniques using Django Celery.

Anyone who is interested and keen to learn Python Celery

What You Need to Know?

Prior knowledge of Django concepts is advantageous.

Prior knowledge of basic Python programming lexicon and concepts is adcentageous

More details

Description
In today's fast-paced web development landscape, efficiently handling time-consuming and resource-intensive tasks is crucial for building high-performance applications. Django Celery, a powerful asynchronous task-processing library, provides the perfect solution to address this challenge. This comprehensive course, "Django Celery Mastery: Python Asynchronous Task Processing," is designed to empower you with the knowledge and skills necessary to harness the full potential of Django Celery and elevate your Python web applications to new heights of scalability and responsiveness.
Course Description: The course begins by guiding you through the process of setting up a fully functional Django Celery working environment. You'll learn the essentials of Django Celery, explore task producers and consumers, and gain hands-on experience building Docker containers for Django, Redis (the message broker), and Celery workers. Additionally, you'll understand the role of a results backend and create a Redis Docker container to facilitate effective task communication.
Moving forward, you'll dive deep into defining and executing Celery tasks within a Django application. You'll discover how to create and register tasks, start and manage Celery workers, and configure task routing for optimized task distribution. Advanced concepts such as task prioritization, task grouping, task chaining, task rate limits, and passing arguments and returning results from Celery tasks will be thoroughly covered. You'll also explore both synchronous and asynchronous task execution approaches and leverage the Flower monitoring tool to track and monitor Celery workers and tasks.
Handling task failures and retries is a critical aspect of asynchronous task processing, and this course provides comprehensive introduction of this topic. You'll gain insights into common types of exceptions and errors in Celery tasks and explore various error handling strategies. You'll implement automatic retries, handle errors in task groups and chains, and discover techniques for handling failed tasks and task timeouts. Additionally, you'll learn how to gracefully shut down tasks, clean up failed tasks, and leverage error tracking and monitoring tools such as Sentry.
Task scheduling and periodic tasks play a vital role in managing recurring tasks efficiently. In this course, you'll understand the fundamentals of task scheduling, including scheduling tasks to run at specific times or intervals. You'll explore the customization of periodic tasks, implement crontab schedules, and ensure schedule persistence in a Django application. Furthermore, you'll learn how to schedule Django custom commands using Celery Beat and monitor service status using custom event tracking and alerting mechanisms.
Throughout the course, hands-on exercises, practical examples, and real-world scenarios will enhance your learning experience and enable you to apply the concepts directly in your own projects. By the end of this course, you'll have gained mastery over Django Celery and be equipped with the skills to implement efficient asynchronous task processing in Python applications, ensuring scalability, responsiveness, and optimal resource utilization.
Whether you are a Python developer, Django developer, web application developer, software engineer, backend developer, or a technical lead/architect, this course will empower you to unlock the full potential of Django Celery and revolutionize your approach to asynchronous task processing. Don't miss this opportunity to level up your skills and supercharge your applications with the power of Celery. Enroll now and take the first step towards mastering asynchronous task processing in Python!

Legal Notice: "Celery Logo" is licensed under the Creative Commons Attribution-Share Alike 4.0 International license. To view a copy of this license, visit creativecommons org licenses by-sa 4.0. No changes were made to the original file. This course is not accredited, certified, affiliated with, or endorsed by Celery Project.

Trademark Usages and Fees Disclosures:
Usage of Django Logo: The Django logo used in this product is for identification purposes only, to signify that the content or service is Django-related. It does not imply that this product is officially endorsed by the Django Software Foundation (DSF) or the Django Core team as representatives of the Django project.
Fees Disclosure: We would like to clarify that 100% of the fees will be retained by the author to support the ongoing development and maintenance of this product. Currently, 0% of the fees, if applicable, will be contributed back to the DSF as a donation to further support the Django community.
Note: The Django name and logo are registered trademarks of the Django Software Foundation, and their usage is subject to the Django Trademark License Agreement.
Usage of Celery Logo: The Celery logo used in this product is for identification purposes only, to signify that the content or service is Celery-Project-related. It does not imply that this product is officially endorsed by the Celery Project or the logo licensor. Author Ty Wilkins - Licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
Who this course is for:
Python Developers: Developers who are already familiar with the Python programming language and want to expand their knowledge and skills in asynchronous task processing using Django Celery.
Django Developers: Developers who are experienced in Django web development and want to incorporate asynchronous task processing into their Django applications to enhance performance and scalability.
Web Application Developers: Professionals involved in web application development who want to learn how to leverage Django Celery for handling time-consuming and resource-intensive tasks asynchronously, such as sending emails, generating reports, or processing large datasets.
Software Engineers: Software engineers interested in learning about task queues and asynchronous processing in Python and Django.
Backend Developers: Backend developers who want to improve the efficiency of their applications by offloading time-consuming tasks to background workers using Django Celery.
Technical Leads and Architects: Technical leads and architects responsible for designing and implementing scalable and performant systems who want to explore asynchronous task processing techniques using Django Celery.
Anyone who is interested and keen to learn Python Celery

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