python主线程和子线程_python 在threading中如何处理主进程和子线程的关系

之前用python的多线程，总是处理不好进程和线程之间的关系。后来发现了join和setDaemon函数，才终于弄明白。下面总结一下。

1.使用join函数后，主进程会在调用join的地方等待子线程结束，然后才接着往下执行。

join使用实例如下：

import time

import random

import threading

class worker(threading.Thread):

def __init__(self):

threading.Thread.__init__(self)

def run(self):

t = random.randint(1,10)

time.sleep(t)

print "This is " + self.getName() + ";I sleep %d second."%(t)

tsk = []

for i in xrange(0,5):

time.sleep(0.1)

thread = worker()

thread.start()

tsk.append(thread)

for tt in tsk:

tt.join()

print "This is the end of main thread."

运行结果如下：

# python testjoin.py

This is Thread-3;I sleep 2 second.

This is Thread-1;I sleep 4 second.

This is Thread-2;I sleep 7 second.

This is Thread-4;I sleep 7 second.

This is Thread-5;I sleep 7 second.

This is the end of main thread.

这里创建了5个子线程，每个线程随机等待1-10秒后打印退出；主线程分别等待5个子线程结束。最后结果是先显示各个子线程，再显示主进程的结果。

2. 如果使用的setDaemon函数，则与join相反，主进程结束的时候不会等待子线程。

setDaemon函数使用实例：

import time

import random

import threading

class worker(threading.Thread):

def __init__(self):

threading.Thread.__init__(self)

def run(self):

t = random.randint(1,10)

time.sleep(t)

print "This is " + self.getName() + ";I sleep %d second."%(t)

tsk = []

for i in xrange(0,5):

time.sleep(0.1)

thread = worker()

thread.setDaemon(True)

thread.start()

tsk.append(thread)

print "This is the end of main thread."

这里设置主进程为守护进程，当主进程结束的时候，子线程被中止

运行结果如下：

#python testsetDaemon.py

This is the end of main thread.

3、如果没有使用join和setDaemon函数，则主进程在创建子线程后，直接运行后面的代码，主程序一直挂起，直到子线程结束才能结束。

import time

import random

import threading

class worker(threading.Thread):

def __init__(self):

threading.Thread.__init__(self)

def run(self):

t = random.randint(1,10)

time.sleep(t)

print "This is " + self.getName() + ";I sleep %d second."%(t)

tsk = []

for i in xrange(0,5):

time.sleep(0.1)

thread = worker()

thread.start()

tsk.append(thread)

print "This is the end of main thread."

运行结果如下：

# python testthread.py

This is the end of main thread.

This is Thread-4;I sleep 1 second.

This is Thread-3;I sleep 7 second.

This is Thread-5;I sleep 7 second.

This is Thread-1;I sleep 10 second.

This is Thread-2;I sleep 10 second.

补充知识：Python Thread和Process对比

原因：进程和线程的差距（方向不同，之针对这个实例）

# coding=utf-8

import logging

import multiprocessing

import os

import time

from threading import Thread

logging.basicConfig(

level=logging.INFO,

format="%(asctime)s 【 %(process)d 】 %(processName)s %(message)s"

)

def func (i):

# logging.info(f'子：{os.getpid()},\t{i}')

return f'子：{os.getpid()},\t{i}'

def main (ctx):

start01 = time.time()

ts = [Thread(target=func, args=(i,)) for i in range(100)]

[t.start() for t in ts]

[t.join() for t in ts]

end01 = time.time() - start01

logging.info(f"线程花费的时间：{end01}秒")

start02 = time.time()

ps = [ctx.Process(target=func, args=(i,)) for i in range(100)]

[p.start() for p in ps]

[p.join() for p in ps]

end02 = time.time() - start02

logging.info(f"进程花费的时间：{end02}秒")

if __name__ == '__main__':

# windows 启动方式

multiprocessing.set_start_method('spawn')

# 获取上下文

ctx = multiprocessing.get_context('spawn')

# 检查这是否是冻结的可执行文件中的伪分支进程。

ctx.freeze_support()

main(ctx)

输出：

2019-10-06 14:17:22,729 【 7412 】 MainProcess 线程花费的时间：0.012967586517333984秒

2019-10-06 14:17:25,671 【 7412 】 MainProcess 进程花费的时间：2.9418249130249023秒

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