Python GIL的一个实验
看了这篇介绍GIL的文章，写的真好，GIL = Global Interpreter Lock, 全局解释器锁，在解释器解释执行任何Python代码时，都需要先获得这把锁才行，也就是一个Python解释器在任意时候都只能跑一个线程，在我的Macbook Pro上跑个实验试试，这些是我本本的参数:
CPU: 2.8 GHz Intel Core i7
➜ Desktop sysctl -a | grep cpu
➜ ~ sysctl -a | grep cpu
hw.ncpu: 4 # 系统使用的cpu数目是4个
hw.activecpu: 4
hw.physicalcpu: 2 # 物理cpu数目是2个
hw.physicalcpu_max: 2
hw.logicalcpu: 4
hw.logicalcpu_max: 4
...
machdep.cpu.brand_string: Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz
...
machdep.cpu.logical_per_package: 16
machdep.cpu.cores_per_package: 8 # 这个不太清楚是啥
...
machdep.cpu.core_count: 2 # 双核
machdep.cpu.thread_count: 4 # 可以跑4线程，即4个Python解释器都跑死循环就能把CPU占到100%
实验很简单了，就是写死循环占cpu，先开一个terminal，运行命令top，查看进程和cpu使用情况，然后不断地开terminal，进python，跑死循环:
➜ ~ python
Python 2.7.10 (default, Oct 17 2015, 01:15:29)
[GCC 4.2.1 Compatible Apple LLVM 6.1.0 (clang-602.0.53)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> while True: pass
...
开1个的时候, top命令显示的CPU usage在25%左右
2个，50%左右
3个，70%左右(好奇为啥没到75%)
4个，98%左右(最大的数看到了99.3%)
5个，98%左右
6个，98%左右
所以在我的机器上一个python解释器只能获得1/4的cpu资源，虐一下自己的机器挺爽的，听到风扇声一下子就起来了，哈哈~ 最后再安利一下Python大法好，写个死循环都只需要一行~
2016年8月04日 10:51
我试了一下，并不能占到四分之一， python3.5
2016年9月02日 01:49
我的是2.7, 系统也要占点资源吧，不能都分给Python吧@tt:
2021年9月30日 13:23
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