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Source channel @githubtrending · Post #14895 · Jul 2

#python#copilot#csharp#dotnet#github#github_copilot#github_copilot_chat#github_copilot_for_azure#github_copilot_free#github_copilot_training#javascript#lab#labs#microsoft#python#sql#tutorial#tutorial_code#tutorial_exercises#visual_studio_code#vscode GitHub Copilot’s new Agent Mode is a powerful AI coding partner that goes beyond just suggesting code—it can independently write, debug, and improve your code, handle complex workflows, and even fix its own mistakes automatically. It works with multiple programming languages and integrates with popular development tools, helping you save time on repetitive tasks like testing, deployment, and refactoring. By using natural language prompts, you can guide it to complete multi-step projects, making coding faster and easier whether you’re a beginner or an expert. This course teaches you how to fully use these features, boosting your productivity and coding skills. https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming

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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,