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Source channel @githubtrending · Post #14794 · Jun 5

#ruby The Model Context Protocol (MCP) is a way to connect AI systems with other tools and data sources securely. It helps developers build AI applications that can interact with external systems more easily. MCP uses a client-server model, allowing AI models to dynamically find and use tools without needing specific code for each integration. This makes it easier to develop and integrate AI applications, reducing the complexity and time needed for setup. Users benefit from more flexible and powerful AI tools that can work with various systems seamlessly. https://github.com/modelcontextprotocol/ruby-sdk

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djangoproject

@djangoproject · Post #439 · 09/13/2017, 03:57 AM

Evented Django part one: Socket.IO and gevent #Socket.IO was developed with a #Node.JS server implementation, but work is being done to add server implementations to a variety of languages. Two such servers exist for Python, tornadio and #gevent-socketio. I'm a big fan of gevent, so I will use gevent-socketio, but tornadio looks well-written and very promising. http://codysoyland.com/2011/feb/6/evented-django-part-one-socketio-and-gevent/

djangoproject

@djangoproject · Post #170 · 09/22/2016, 02:27 PM

https://pypi.python.org/pypi/uvloop #uvloop is a fast, drop-in replacement of the built-in #asyncio event loop. uvloop is released under the MIT license. uvloop and asyncio, combined with the power of async/await in Python 3.5, makes it easier than ever to write high-performance #networking code in Python. uvloop makes asyncio fast. In fact, it is at least 2x faster than #nodejs, #gevent, as well as any other Python #asynchronous framework. The performance of uvloop-based asyncio is close to that of Go programs.

djangoproject

@djangoproject · Post #270 · 02/26/2017, 08:08 AM

https://www.obeythetestinggoat.com/testing-async-asyncio-and-performance.html #Testing, #async, #asyncio, and #performance Sun 27 December 2015 By Harry I recently did some experimenting with asyncio, and wanted to report back on how I got on with writing tests for it. While I was at it I was also able to compare its performance with a couple of other approaches to #mutlitasking in Python, namely #threads and #gevent, so I'll report on that here too. (tl;dr: it's much of a muchness).