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Source channel @githubtrending · Post #14953 · Jul 13

#python#documentation#gotchas#interview_questions#pitfalls#python#python_interview_questions#snippets#wats#wtf Python is a high-level, easy-to-read programming language widely used in many fields like web development, data science, and AI. The "What the f*ck Python?" project helps you understand tricky, surprising Python behaviors through clear examples and explanations. It reveals lesser-known features and common pitfalls, making it easier to write better code and debug problems. By exploring these examples, you can deepen your knowledge of Python’s internals, improve your coding skills, and avoid common mistakes, which benefits both beginners and experienced programmers alike[3]. https://github.com/satwikkansal/wtfpython

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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,