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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 #118 · 08/08/2016, 11:44 AM

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,