Python Celery Distributed Task Queue | End to End Application with Celery скачать в хорошем качестве

Python Celery Distributed Task Queue | End to End Application with Celery

Software systems of the modern world makes use of distributed systems for multiple task which needs to be executed outside the core system functionalities and are not real time in nature. These systems communicate with each other using things like message queues, event streaming and /or publish subscribe architecture. There are many softwares which can be used for thing including but not limited to Apache Kafka, rabbitMQ, Kinesis and google pub sub etc and all of them can be used effectively and effeciently over here. However, in this video I'm introducing you to celery. a simple, flexible, fast and pure python system to create scalable distributed task where tasks and execute in different distributed system in asynchronous and /or synchronous way. In this video, I've talked about about basics of task queues and under what all scenarios we can create task queues. This is followed by using RabbitMQ as a messaging broker and then using simple python client and server. After watching this video, you'll understand how to Create a celery program concerpts of the workers of a celery program getting the results back in the python code triggering async execution of the tasks I do hope that this video will help you in your learning journey, Thanks for watching Timecodes 00:00 Apache Kafka, RabbitMQ, Kinesis and Pub Sub 00:57 Why we use Distributed Systems 02:43 The Concept of Task Queues 03:24 Celery Distributed Task Queue 04:22 Celery Version and Python Compatibility 04:36 using Celery with RabbitMQ 05:36 RabbitMQ Management using Docker container 05:58 Creating basic celery task 07:21 Celery Client 07:41 Running Celery with workers 08:21 Running celery task from a python client 08:48 Calling Celery with Delay function 10:23 Celery workers and multiple processes 14:01 Celery Concurrency 15:43 Reliability of Celery - Celery restart and finish items in the RabbitMQ 17:11 Returning results in the celery to the client 19:03 Waiting for results in Celery #celery #distributedsystems #python #pythonprogramming #CognitiveProgrammer