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Source channel @githubtrending · Post #15499 · Feb 17

#typescript#ai#cli#summarize#typescript Summarize is a fast tool for summarizing URLs, PDFs, images, audio/video, YouTube, and podcasts via Chrome Side Panel (with chat and history), Firefox Sidebar, or CLI. Install the extension from Chrome Web Store, add the local daemon with `npm i -g @steipete/summarize` and `summarize daemon install --token <TOKEN>`, then get one-click summaries, YouTube slides with OCR/timestamps, streaming Markdown, and media transcription. It saves time by quickly digesting long content so you focus on key insights without reading everything. https://github.com/steipete/summarize

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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,