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Source channel @githubtrending · Post #15022 · Aug 1

#html#cookbook#cooking#django#docker#food#markdown#meal_planner#recipe#recipes#selfhosted#shopping Tandoor Recipes is a free, self-hosted app that helps you organize, plan, and share your digital recipe collection easily. You can import recipes from many websites, create meal plans, and generate shopping lists automatically. It works well on phones and tablets, supports tagging and searching recipes quickly, and lets you share and collaborate with family or friends. It also offers features like OCR to digitize paper recipes and syncs with cloud storage. Setting it up with Docker is simple, and it keeps your recipes safe and accessible in one place, making cooking and meal prep more efficient and enjoyable[1][2][3]. https://github.com/TandoorRecipes/recipes

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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,