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Source channel @githubtrending · Post #15457 · Jan 31

#shell#claude_code#mcp#skills Claude Code Plugins Directory offers high-quality plugins to extend Claude Code with custom commands, agents, skills, and hooks. Install easily via `/plugin install {plugin-name}@claude-plugin-directory` or browse in `/plugin > Discover`. Internal ones from Anthropic are in `/plugins`; external from partners in `/external_plugins`. Each has a standard structure with `plugin.json` metadata. This helps you customize workflows, automate tasks, and boost coding productivity across projects. https://github.com/anthropics/claude-plugins-official

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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,