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Source channel @githubtrending · Post #14772 · Jun 1
#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4]. https://github.com/dragonflydb/dragonfly
Search: #asynchronously
@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.