VB.net 2010 视频教程 VB.net 2010 视频教程 python基础视频教程
SQL Server 2008 视频教程 c#入门经典教程 Visual Basic从门到精通视频教程
当前位置:
首页 > Python基础教程 >
  • python 在threading中如何处理主进程和子线程的关系

这篇文章主要介绍了python 在threading中如何处理主进程和子线程的关系,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧

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。

  1. 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

以上这篇python 在threading中如何处理主进程和子线程的关系就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持。

原文链接:https://blog.csdn.net/oatnehc/article/details/50616835


相关教程