下面代码是《python核心编程》关于多线程编程一章中的一个例子:
#!/usr/bin/env python
import threading
from time import sleep, ctime
loops = [ 4, 2 ]
class MyThread(threading.Thread):
def __init__(self, func, args, name=''):
threading.Thread.__init__(self)
self.name = name
self.func = func
self.args = args
def run(self):
apply(self.func, self.args)
def loop(nloop, nsec):
print 'start loop', nloop, 'at:', ctime()
sleep(nsec)
print 'loop', nloop, 'done at:', ctime()
def main():
print 'starting at:', ctime()
threads = []
nloops = range(len(loops))
for i in nloops:
t = MyThread(loop, (i, loops[i]),
loop.__name__)
threads.append(t)
for i in nloops:
threads[i].start()
for i in nloops:
threads[i].join()
print 'all DONE at:', ctime()
if __name__ == '__main__':
main()
书上显示的输出结果是这样的
我自己打了一遍,输出结果是这样的
可以看到,我的loop0和loop1的显示内容混合到一起了,这样是对的吗?为什么会这样?
You need to lock it here. The standard output is a shared resource. Everyone can write to the screen at the same time, so it may be confusing.
TheYou need to add a mutex lock here to tell other threads that I want to write now, so don’t write it yet. Then when you finish writing, tell other threads that I have finished writing, and you can apply to write.
loop function is written as:
All codes are:
Three knowledge points are involved here
Python thread scheduling strategy
Python threads are actually native threads supported by the operating system. Python's multi-threading mechanism is based on the native thread mechanism of the operating system. Different operating systems have different implementations
window/linux python thread scheduling strategy
Search for "window thread scheduling strategy" or "linux thread scheduling strategy"
python GIL lock - PYTHON single process without parallelism
Then you will understand
You can understand after running it a few times