@djangoproject · Post #585 · 03/23/2018, 02:43 AM
https://www.fullstackpython.com/celery.html #Celery is a task #queue implementation for Python web applications used to #asynchronously execute work outside the HTTP request-response cycle.
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Source channel @githubtrending · Post #14648 · Apr 30
#java#ai#apache_kafka#aws#azure#cloud#cloud_first#cloud_native#ebs#gcp#kafka#llm#messaging#minio#s3#serverless#spot#streaming AutoMQ provides a cloud-native alternative to Apache Kafka that runs on S3 storage, cutting costs by up to 90% while enabling instant scaling and eliminating cross-zone traffic fees. It offers high reliability, serverless operation, and full Kafka compatibility, making it easier and cheaper to manage large-scale data streaming without sacrificing performance or features. https://github.com/AutoMQ/automq
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@djangoproject · Post #585 · 03/23/2018, 02:43 AM
https://www.fullstackpython.com/celery.html #Celery is a task #queue implementation for Python web applications used to #asynchronously execute work outside the HTTP request-response cycle.
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@djangoproject · Post #262 · 02/16/2017, 07:24 AM
http://masnun.com/2015/11/20/python-asyncio-future-task-and-the-event-loop.html On any platform, when we want to do something #asynchronously, it usually involves an #event loop. An event loop is a loop that can register #tasks to be executed, execute them, delay or even cancel them and handle different events related to these operations. Generally, we #schedule multiple async functions to the event loop. The loop runs one function, while that function waits for #IO, it pauses it and runs another. When the first function completes IO, it is resumed. Thus two or more functions can #co_operatively run together. This the main goal of an event loop.