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python threading主进程子线程 python 在threading中怎样处理主进程和子线程的关系

chen_999876 人气:2

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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