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Source channel @githubtrending · Post #15162 · Sep 21

#c_lang You can find detailed guides for Linux kernel developers and users in the Documentation/ folder, with files in formats like HTML and PDF. To build these documents yourself, use commands like `make htmldocs` or `make pdfdocs`. The documentation covers important topics such as kernel building, running requirements, and upgrade issues. Reading these helps you understand how to work with the Linux kernel safely and effectively, avoiding common problems when upgrading or modifying it. This makes managing and developing the kernel easier and more reliable for you. https://github.com/torvalds/linux

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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,