TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15114 · Sep 3

#kotlin#android#apk#apks#dhizuku#installer#root#shizuku InstallerX Revived is a free, open-source Android app installer that replaces your phone’s default installer with a more powerful and customizable one. It supports many file types like apk, apks, xapk, and zip with multiple apps inside. You get features like batch installs, automatic deletion of install files, and options to block certain apps from installing. It works on Android 7 to 16 and offers a modern interface with language support. This installer improves installation speed, fixes bugs, and lets you control installation settings for a smoother, safer app installation experience. It’s community-maintained and respects your privacy. https://github.com/wxxsfxyzm/InstallerX-Revived

Results

1 similar post found

Search: #parallelism

当前筛选 #parallelism清除筛选
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,