d(・ω・d) 微分！(∫・ω・)∫ 積分！∂(・ω・∂) 偏微分！(∮・ω・)∮ 沿閉曲線的積分！(∬・ω・)∬ 重積分！∇(・ω・∇)梯度！∇・(・ω・∇・)散度！∇×(・ω・∇×)旋度！Δ(・ω・Δ)拉普拉斯！#ﾟÅﾟ）⊂彡☆))ﾟДﾟ)･∵ლ(◉◞౪◟◉ )ლ千言萬語，不如一個「表情符號(emoji)」簡單生動又有趣!ಠ▃ಠ生氣、-`д´-憤怒、(¬_¬)無言、(•͈⌔•͈⑅)傷心、哭、開心、大笑、可愛、困惑、發呆、大眼睛、驚呀、跳舞、興奮、奔跑..≧Д≦ （;≧皿≦） (⁎˃ᆺ˂) ╬ Ò ‸ Ó) <(｀^´)> ( >д<) (ꐦ ಠ皿ಠ ) (｀Д´) (;｀O´)o o(-`д´- ｡) ( ˃⌂˂ ) (°ㅂ° ╬) (ʘ言ʘ╬) (Ò 皿 Ó ╬) (-`д´-) 눈_눈 (⋋▂⋌) (¬▂¬) ಠ▃ಠ (＞x＜) ╰（‵□′）╯ D.R.S Dz

Sindbad~EG File Manager

Current Path : /lib64/python3.9/asyncio/
Upload File :
Current File : //lib64/python3.9/asyncio/threads.py

"""High-level support for working with threads in asyncio"""

import functools
import contextvars

from . import events


__all__ = "to_thread",


async def to_thread(func, /, *args, **kwargs):
    """Asynchronously run function *func* in a separate thread.

    Any *args and **kwargs supplied for this function are directly passed
    to *func*. Also, the current :class:`contextvars.Context` is propagated,
    allowing context variables from the main thread to be accessed in the
    separate thread.

    Return a coroutine that can be awaited to get the eventual result of *func*.
    """
    loop = events.get_running_loop()
    ctx = contextvars.copy_context()
    func_call = functools.partial(ctx.run, func, *args, **kwargs)
    return await loop.run_in_executor(None, func_call)

Sindbad File Manager Version 1.0, Coded By Sindbad EG ~ The Terrorists