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Изворен канал @pythonotes · Post #422 · 30 мар.

Если запустить REPL с модулем asyncio, то вы входите в особый асинхронный REPL. user@host:~$ python -m asyncio asyncio REPL 3.12.7 ... Use "await" directly instead of "asyncio.run()". >>> import asyncio >>> В этом режиме - создаётся и настраивается event loop - уже импортирован asyncio - работает await на верхнем уровне То есть такая команда сработает без ошибок! await asyncio.sleep(3) Удобно для тестирования асинхронных функций без создания ивентлупов и остальной обвязки. Работает в: 3.8+ #tricks#async

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djangoproject

@djangoproject · Post #118 · 08.08.2016 г., 11:44

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,