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Source channel @githubtrending · Post #15079 · Aug 20

#typescript#svelte#sveltekit#tailwindcss#tauri Epicenter is a free, open-source set of local-first apps that let you own and control your data by storing everything—notes, transcripts, chats—in one simple folder using plain text and SQLite. You can use any AI model you want, customize tools, and access your data anywhere without relying on cloud services. Key apps include Whispering, which transcribes your speech locally, and epicenter.sh, a personal assistant that helps you search and interact with your data. This setup gives you privacy, flexibility, and full control over your information, avoiding locked, siloed apps and data traps. It’s great for anyone who values data ownership and open software. https://github.com/epicenter-so/epicenter

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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,