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Source channel @githubtrending · Post #15551 · Mar 9

#python#agentic_ai#agentic_coding#ai_coding_agent#ai_plugins#anthropic_claude#claude_ai#claude_ai_skills#claude_code#claude_code_plugins#claude_code_skills#claude_skills#claudecode_subagents#developer_tools#devtools#mcp_tools#openai_codex#prompt_engineering Claude Code Skills offers 169 free, ready-to-use plugins that turn AI coding agents like Claude Code, OpenAI Codex, and OpenClaw into experts in engineering, marketing, product, compliance, and more. Install easily via simple commands to add skills like security auditing, test automation, or C-level advice, with 160+ Python tools included. This saves you time by automating complex tasks, boosting code quality, and handling grunt work so you focus on creative problem-solving and faster results. https://github.com/alirezarezvani/claude-skills

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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,