网站制作开发平台,怎么做旅行网站,西安 网站搭建,系统开发必须遵守的原则有哪些Python多线程编程中常用方法#xff1a;
1、join()方法#xff1a;如果一个线程或者在函数执行的过程中调用另一个线程#xff0c;并且希望待其完成操作后才能执行#xff0c;那么在调用线程的时就可以使用被调线程的join方法join([timeout]) timeout#xff1a;可选参数…Python多线程编程中常用方法
1、join()方法如果一个线程或者在函数执行的过程中调用另一个线程并且希望待其完成操作后才能执行那么在调用线程的时就可以使用被调线程的join方法join([timeout]) timeout可选参数线程运行的最长时间
2、isAlive()方法查看线程是否还在运行
3、getName()方法获得线程名
4、setDaemon()方法主线程退出时需要子线程随主线程退出则设置子线程的setDaemon()
Python线程同步
1Thread的Lock和RLock实现简单的线程同步
import threading
import time
class mythread(threading.Thread):def __init__(self,threadname):threading.Thread.__init__(self,namethreadname)def run(self):global xlock.acquire()for i in range(3):x x1time.sleep(1)print xlock.release()if __name__ __main__:lock threading.RLock()t1 []for i in range(10):t mythread(str(i))t1.append(t)x 0for i in t1:i.start()
2使用条件变量保持线程同步
# codingutf-8
import threadingclass Producer(threading.Thread):def __init__(self,threadname):threading.Thread.__init__(self,namethreadname)def run(self):global xcon.acquire()if x 10000:con.wait() passelse:for i in range(10000):x x1con.notify()print xcon.release()class Consumer(threading.Thread):def __init__(self,threadname):threading.Thread.__init__(self,namethreadname)def run(self):global xcon.acquire()if x 0:con.wait()passelse:for i in range(10000):x x-1con.notify()print xcon.release()if __name__ __main__:con threading.Condition()x 0p Producer(Producer)c Consumer(Consumer)p.start()c.start()p.join()c.join()print x
3使用队列保持线程同步
# codingutf-8
import threading
import Queue
import time
import randomclass Producer(threading.Thread):def __init__(self,threadname):threading.Thread.__init__(self,namethreadname)def run(self):global queuei random.randint(1,5)queue.put(i)print self.getName(), put %d to queue %(i)time.sleep(1)class Consumer(threading.Thread):def __init__(self,threadname):threading.Thread.__init__(self,namethreadname)def run(self):global queueitem queue.get()print self.getName(), get %d from queue %(item)time.sleep(1)if __name__ __main__:queue Queue.Queue()plist []clist []for i in range(3):p Producer(Producerstr(i))plist.append(p)for j in range(3):c Consumer(Consumerstr(j))clist.append(c)for pt in plist:pt.start()pt.join()for ct in clist:ct.start()ct.join()
生产者消费者模式的另一种实现
# codingutf-8
import time
import threading
import Queueclass Consumer(threading.Thread):def __init__(self, queue):threading.Thread.__init__(self)self._queue queuedef run(self):while True:# queue.get() blocks the current thread until an item is retrieved.msg self._queue.get()# Checks if the current message is the quitif isinstance(msg, str) and msg quit:# if so, exists the loopbreak# Processes (or in our case, prints) the queue itemprint Im a thread, and I received %s!! % msg# Always be friendly!print Bye byes!class Producer(threading.Thread):def __init__(self, queue):threading.Thread.__init__(self)self._queue queuedef run(self):# variable to keep track of when we startedstart_time time.time()# While under 5 seconds..while time.time() - start_time 5:# Produce a piece of work and stick it in the queue for the Consumer to processself._queue.put(something at %s % time.time())# Sleep a bit just to avoid an absurd number of messagestime.sleep(1)# This the quit message of killing a thread.self._queue.put(quit)if __name__ __main__:queue Queue.Queue()consumer Consumer(queue)consumer.start()producer1 Producer(queue)producer1.start()
使用线程池Thread pool同步队列Queue的实现方式
# A more realistic thread pool example
# codingutf-8
import time
import threading
import Queue
import urllib2 class Consumer(threading.Thread): def __init__(self, queue):threading.Thread.__init__(self)self._queue queue def run(self):while True: content self._queue.get() if isinstance(content, str) and content quit:breakresponse urllib2.urlopen(content)print Bye byes!def Producer():urls [http://www.python.org, http://www.yahoo.comhttp://www.scala.org, http://cn.bing.com# etc.. ]queue Queue.Queue()worker_threads build_worker_pool(queue, 4)start_time time.time()# Add the urls to processfor url in urls: queue.put(url) # Add the quit messagefor worker in worker_threads:queue.put(quit)for worker in worker_threads:worker.join()print Done! Time taken: {}.format(time.time() - start_time)def build_worker_pool(queue, size):workers []for _ in range(size):worker Consumer(queue)worker.start() workers.append(worker)return workersif __name__ __main__:Producer()
另一个使用线程池Map的实现
import urllib2
from multiprocessing.dummy import Pool as ThreadPool urls [http://www.python.org, http://www.python.org/about/,http://www.python.org/doc/,http://www.python.org/download/,http://www.python.org/community/]# Make the Pool of workers
pool ThreadPool(4)
# Open the urls in their own threads
# and return the results
results pool.map(urllib2.urlopen, urls)
#close the pool and wait for the work to finish
pool.close()
pool.join()
