|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/django-celery-mastery/
课程评论：没有评论
课程名称：Django Celery 精通：Python 异步任务处理 课程概述： 在快速发展的网络开发环境中，高效处理耗时且资源密集的任务对于构建高性能应用至关重要。Django Celery是一个强大的异步任务处理库，为解决这一挑战提供了完美的解决方案。本课程旨在帮助您掌握Django Celery的全部潜力，使您的Python网络应用在可扩展性和响应性方面达到新的高度。 课程内容： 课程开始时，您将学习如何建立一个完整的Django Celery工作环境。内容包括Django Celery的基础知识、任务生产者和消费者，并通过构建Django、Redis（消息中介）和Celery工作者的Docker容器获得实践经验。此外，您将理解结果后端的角色，并创建一个Redis Docker容器以促进有效的任务通信。 接下来，您将深入定义和执行Django应用中的Celery任务。您将学习如何创建和注册任务、启动和管理Celery工作者，并配置任务路由以优化任务分配。课程还将详细讲解高级概念，如任务优先级、任务分组、任务链、任务速率限制，以及如何传递参数和返回Celery任务的结果。您还将探索同步和异步任务执行的方法，并使用Flower监控工具跟踪Celery工作者和任务。 课程还将提供关于处理任务失败和重试的全面介绍，帮助您理解Celery任务中的常见异常和错误，以及各种错误处理策略。您将实施自动重试，处理任务组和链中的错误，并探索处理失败任务和任务超时的技巧。此外，您将学习如何优雅地关闭任务、清理失败任务，并利用错误跟踪和监控工具（如Sentry）。 任务调度和定期任务在高效管理重复任务方面发挥着重要作用。本课程将帮助您理解任务调度的基本原理，包括定时或间隔运行任务的调度。您将探索定期任务的定制，实现crontab计划，并确保在Django应用中的调度持久性。此外，您还将学习如何使用Celery Beat调度Django自定义命令，以及使用自定义事件跟踪和警报机制监控服务状态。 通过动手练习、实际案例和真实场景，您将完善学习体验，并将概念直接应用于自己的项目中。课程结束时，您将熟练掌握Django Celery，并具备在Python应用中实施高效异步任务处理的技能，从而确保可扩展性、响应性和资源的最佳利用。 无论您是Python开发者、Django开发者、Web应用开发者、软件工程师、后端开发者，还是技术负责人/架构师，这门课程都将帮助您充分发挥Django Celery的潜力，彻底改革您对异步任务处理的看法。现在就报名，迈出掌握Python异步任务处理的第一步吧！
Udemy Business Users:This course requires you to download software Python from the official python website and Docker Desktop from official docker website. If you are a Udemy Business user, please check with your employer before downloading software.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.
