TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #14840 · Jun 19

#other This collection of Alfred workflows lets you automate many tasks on your Mac, like showing charger power, generating random images, fixing zoom issues, editing SVGs, converting CSS styles, managing Git projects, switching audio devices, and more. These workflows save you time by performing complex or repetitive actions with simple commands or shortcuts. For example, you can quickly clone Git repos, switch audio inputs, or convert timestamps without leaving your keyboard. Using these tools boosts your productivity by making your computer easier and faster to control, especially if you use Alfred’s Powerpack to integrate and customize workflows for your needs[1][2][5]. https://github.com/sunzsh/favoritesWorkflow4Alfred

Hashtags

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,