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+--- Thread: Django Celery Mastery: Python Asynchronous Task Processing (/Thread-Django-Celery-Mastery-Python-Asynchronous-Task-Processing)
Django Celery Mastery: Python Asynchronous Task Processing - Farid - 01-15-2025
![[Image: 6349ff906e96342d911813ced2609db5.jpg?r=1]](https://i124.fastpic.org/big/2025/0115/b5/6349ff906e96342d911813ced2609db5.jpg?r=1)
Year of manufacture : 2023
Manufacturer : Udemy
Manufacturer's website : Author : Very Academy
Duration : ~7h50m
Type of material distributed : Video lesson
Language : En
Описание: 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!
Content
00:41
Code Examples
00:05
05:34
07:18
[Windows] Creating Virtual Environments
09:23
[macOS] Visual Studio Code Induction
07:55
[macOS] Installing Python
05:49
[macOS] Creating Virtual Environments
04:56
Docker Installation
00:55
10:21
02:28
33:54
Building a Redis Docker Container
01:34
Introducing Task consumers (Workers)
03:35
Building a Celery Worker Docker Container
03:02
Introducing Results Backend
07:49
Creating and Registering Celery Tasks in Django
12:57
Starting the Celery Worker
04:09
Initiating a Celery Task
10:50
Creating a new standalone Celery Worker
17:36
Introducing Tasks Routing
06:00
Configuring Task Routing
11:34
Introducing Celery Task Prioritization
03:01
Configuring Task Prioritization (Redis)
10:56
The Primitives - Task Grouping
04:37
The Primitives - Task Chaining
04:24
Task Rate limits
05:28
Configuring Task Prioritization (RabbitMQ)
21:45
Passing arguments and returning results from Celery tasks
09:33
Executing tasks synchronously and asynchronously
07:52
Monitoring Celery Workers and Tasks with Flower
11:09
Common Types of Exceptions and Errors in Celery Tasks
04:41
Dynamic Task Discovery in Celery: Auto-discovering Tasks in a Directory
16:14
Error Handling: Try Except Blocks
14:27
Handling Errors in Celery Tasks with Custom Task Classes
12:16
Implementing Automatic Retries
07:35
Error Handling in Groups
13:29
Towards Error Handling in Task Chains
06:35
Towards Dead-letter Queues: Handling Failed Tasks
17:42
Task Timeouts and Task Revoking (Using task time limits and timeouts)
17:09
Handling Errors in Task Result Callbacks
09:18
Task Signals Graceful Shutdown and Cleanup of Failed Tasks
09:10
Error Tracking and Monitoring with Sentry
12:07
Introduction to Task Scheduling
06:10
Scheduling Tasks to Run at Specific Times or Intervals
10:28
Implementing Periodic Tasks Customization
05:18
Crontab Schedules
05:25
Implement Schedule Persistence for Celery in a Django Application
14:00
Schedule a Django Custom Command with Celery Beat
14:51
Monitoring Service Status Including Custom Event Tracking and Alerting
25:26
Example files : present
Video format : MP4
Video : AVC, 1280x720, 16:9, 30fps, ~400kbps
Audio : AAC, 48kHz, 128kbps, stereo
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📌 Udemy - Django Celery Mastery Python Asynchronous Task Processing (3.63 GB)
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