Python 提供了几个用于多线程编程的模块，包括thread, threading 和Queue 等。thread 和threading 模块允许程序员创建和管理线程。thread 模块提供了基本的线程和锁的支持，而threading提供了更高级别，功能更强的线程管理的功能。Queue 模块允许用户创建一个可以用于多个线程之间共享数据的队列数据结构。
注意：避免使用thread模块，因为它不支持守护线程。当主线程退出时，所有的子线程不论它们是否还在工作，都会被强行退出。下面重点说说threading模块。我们的多线程继承threading模块里的Thread类，它的主要函数有：
例子一：
import threading
class http_call:
def __init__(self):
self.state = ''
def get_vm_info(self):
self.state = 'get_vm_info_done'
print self.state
def hhb(self):
self.state = 'hhb'
print self.state
if __name__ == '__main__':
#global hrc
hrc = http_call()
thread1 = threading.Thread(target=hrc.get_vm_info)
thread1.setDaemon(True)
thread1.start()
#thread = threading.Thread(target=hrc.start_vm, args=(vmid,))
thread2 = threading.Thread(target=hrc.hhb)
thread2.setDaemon(True)
thread2.start()
例子二，加入了队列：
import Queue
import threading
import urllib2
import time
#from BeautifulSoup import BeautifulSoup
hosts = ["http://yahoo.com", "http://google.com", "http://amazon.com",
"http://ibm.com", "http://apple.com"]
queue = Queue.Queue()
out_queue = Queue.Queue()
class ThreadUrl(threading.Thread):
"""Threaded Url Grab"""
def __init__(self, queue, out_queue):
threading.Thread.__init__(self)
self.queue = queue
self.out_queue = out_queue
def run(self):
while True:
#grabs host from queue
host = self.queue.get()
#grabs urls of hosts and then grabs chunk of webpage
url = urllib2.urlopen(host)
chunk = url.read()
#place chunk into out queue
self.out_queue.put(chunk)
#signals to queue job is done
self.queue.task_done()
class DatamineThread(threading.Thread):
"""Threaded Url Grab"""
def __init__(self, out_queue):
threading.Thread.__init__(self)
self.out_queue = out_queue
def run(self):
while True:
#grabs host from queue
chunk = self.out_queue.get()
print chunk
#parse the chunk
#soup = BeautifulSoup(chunk)
#print soup.findAll(['title'])
#signals to queue job is done
self.out_queue.task_done()
start = time.time()
def main():
#spawn a pool of threads, and pass them queue instance
for i in range(5):
t = ThreadUrl(queue, out_queue)
t.setDaemon(True)
t.start()
#populate queue with data
for host in hosts:
queue.put(host)
for i in range(5):
dt = DatamineThread(out_queue)
dt.setDaemon(True)
dt.start()
#wait on the queue until everything has been processed
queue.join()
out_queue.join()
main()
print "Elapsed Time: %s" % (time.time() - start)
'''
-*- coding: utf-8 -*-
@author: intple
'''
from multiprocessing import Process
import os
def f(name):
print('hello', name)
print('process id:' ,os.getpid())
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
p2 = Process(target=f, args=('hhb',))
p2.start()
p2.join()
#-进程-######################################################
'''
-*- coding: utf-8 -*-
@author: intple
'''
from multiprocessing import Process
import os
def f(name):
print('hello', name)
print('process id:' ,os.getpid())
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
p2 = Process(target=f, args=('hhb',))
p2.start()
p2.join()
#-线程-######################################################
'''
-*- coding: utf-8 -*-
@author: intple
'''
import threading
class http_call:
def __init__(self):
self.func = ''
def get_vm_info(self, a2):
self.func = 'get_vm_info_done'
print self.func
print a2
def hhb(self, a2):
self.state = 'hhb'
print self.func
print a2
if __name__ == '__main__':
#global hrc
hrc = http_call()
# thread1
thread1 = threading.Thread(target=hrc.get_vm_info(13))
thread1.setDaemon(True)
thread1.start()
# thread2
thread2 = threading.Thread(target=hrc.get_vm_info(16))
thread2.setDaemon(True)
thread2.start()