在"Advanced Options"下,确保选择“Download free-threaded binaries(experimental)”选项,然后点击“安装”。 安装完成后,在安装目录下回有一个python3.13t.exe 的程序,这个就是无GIL 自由线程版本的入口。 测试多线程 下面代码创建并启动四个线程以并行执行一个模拟 CPU 密集任务的函数,并计算
测试Python3.13的no-GIL真多线程版本性能 先去官网下载3.13安装版本,我使用的是Python 3.13.1。 安装在windows下需要选择多线程版本的下载(free-threaded),不然你要自己编译。 安装好后,比正常python在目录下面多了下面的几个文件,都是加了一个t在后面: python3.13t.exe python313t.dll pythonw3.13t.exe 写一段...
regular CI job for free-threaded CPython on Linux:CI: Add Linux workflow to test on free-threaded Python builds#20822 wheel builds for: Linux (manylinuxandmusllinux):CI: Add workflow to build and upload free-threaded wheels#20882 macOS (4x:x86-64andarm64, with OpenBLAS and Accelerate):CI...
Python 开发团队计划将 no-GIL 的实现分为三个阶段: 实验阶段:提供 build-time 选项,让开发者在构建时选择启用自由线程(free-threaded)。此阶段明确告知是实验性的,不支持用于生产环境。 支持但不默认阶段:在 API 和ABI 变更充分解决,并且有足够的社区支持时开始启动。 默认阶段:默认启用自由线程(初期仍支持禁用)...
实验阶段。通过提供 build-time 选项,让开发者在构建时选择启用自由线程 (free-threaded)。在此阶段对外明确告知是实验性的,不支持用于生产环境。 支持但不默认阶段。该阶段将在 API 和 ABI 变更充分解决,并且有足够的社区支持时开始启动。 默认阶段。此时默认启用自由线程(初期仍支持禁用),但此阶段确切的标准很难...
A central repository to keep track of the status of work on and support for free-threaded CPython (see PEP 703), with a focus on the scientific and ML/AI ecosystem - AA-Turner/free-threaded-compatibility
方便判断线程数量 self.free_thread_list=[]# 空闲线程数 defrun(self,function,args,callback=None):''':paramfunction:执行函数:param args:要执行的函数的参数,定义为元组传参:param callback:回调函数,TorF的返回值:return:''' # 判断是否创建真实线程iflen(self.free_thread_list)==0andlen(self....
Otherwise (block is false), put an item on the queue if a free slot is immediately available, else raise the Full exception (timeout is ignored in that case). Queue.put_nowait(item) Equivalent to put(item, False). Queue.get(block=True, timeout=None) Remove and return an item from ...
"""Threaded Url Grab""" def __init__(self, queue): threading.Thread.__init__(self) self.queue = queue def run(self): while True: #grabs host from queue host = self.queue.get() #grabs urls of hosts and prints first 1024 bytes of page ...
This is because Python is a single-threaded runtime. For a function app that processes a large number of I/O events or is being I/O bound, you can significantly improve performance by running functions asynchronously. For more information, see Improve throughout performance of Python apps in ...