标签:opened 进程池 urllib2 工作 大量 序列 log exe running
Threading用于提供线程相关的操作,线程是应用程序中工作的最小单元。
#!/usr/bin/env python # -*- coding:utf-8 -*- import threading import time def show(arg): time.sleep(1) print ‘thread‘+str(arg) for i in range(10): t = threading.Thread(target=show, args=(i,)) t.start() print ‘main thread stop‘
上述代码创建了10个“前台”线程,然后控制器就交给了CPU,CPU根据指定算法进行调度,分片执行指令。
更多方法:
import threading import time class MyThread(threading.Thread): def __init__(self,num): threading.Thread.__init__(self) self.num = num def run(self):#定义每个线程要运行的函数 print("running on number:%s" %self.num) time.sleep(3) if __name__ == ‘__main__‘: t1 = MyThread(1) t2 = MyThread(2) t1.start() t2.start()
线程锁(Lock、RLock)
由于线程之间是进行随机调度,并且每个线程可能只执行n条执行之后,当多个线程同时修改同一条数据时可能会出现脏数据,所以,出现了线程锁 - 同一时刻允许一个线程执行操作。
#!/usr/bin/env python # -*- coding:utf-8 -*- import threading import time gl_num = 0 def show(arg): global gl_num time.sleep(1) gl_num +=1 print gl_num for i in range(10): t = threading.Thread(target=show, args=(i,)) t.start() print ‘main thread stop‘
#!/usr/bin/env python #coding:utf-8 import threading import time gl_num = 0 lock = threading.RLock() def Func(): lock.acquire() global gl_num gl_num +=1 time.sleep(1) print gl_num lock.release() for i in range(10): t = threading.Thread(target=Func) t.start()
信号量(Semaphore)
互斥锁 同时只允许一个线程更改数据,而Semaphore是同时允许一定数量的线程更改数据 ,比如厕所有3个坑,那最多只允许3个人上厕所,后面的人只能等里面有人出来了才能再进去。
import threading,time def run(n): semaphore.acquire() time.sleep(1) print("run the thread: %s" %n) semaphore.release() if __name__ == ‘__main__‘: num= 0 semaphore = threading.BoundedSemaphore(5) #最多允许5个线程同时运行 for i in range(20): t = threading.Thread(target=run,args=(i,)) t.start()
事件(event)
python线程的事件用于主线程控制其他线程的执行,事件主要提供了三个方法 set、wait、clear。
事件处理的机制:全局定义了一个“Flag”,如果“Flag”值为 False,那么当程序执行 event.wait 方法时就会阻塞,如果“Flag”值为True,那么event.wait 方法时便不再阻塞。
#!/usr/bin/env python # -*- coding:utf-8 -*- import threading def do(event): print ‘start‘ event.wait() print ‘execute‘ event_obj = threading.Event() for i in range(10): t = threading.Thread(target=do, args=(event_obj,)) t.start() event_obj.clear() inp = raw_input(‘input:‘) if inp == ‘true‘: event_obj.set()
条件(Condition)
使得线程等待,只有满足某条件时,才释放n个线程
import threading def run(n): con.acquire() con.wait() print("run the thread: %s" %n) con.release() if __name__ == ‘__main__‘: con = threading.Condition() for i in range(10): t = threading.Thread(target=run, args=(i,)) t.start() while True: inp = input(‘>>>‘) if inp == ‘q‘: break con.acquire() con.notify(int(inp)) con.release()
def condition_func(): ret = False inp = input(‘>>>‘) if inp == ‘1‘: ret = True return ret def run(n): con.acquire() con.wait_for(condition_func) print("run the thread: %s" %n) con.release() if __name__ == ‘__main__‘: con = threading.Condition() for i in range(10): t = threading.Thread(target=run, args=(i,)) t.start()
Timer
定时器,指定n秒后执行某操作
from threading import Timer def hello(): print("hello, world") t = Timer(1, hello) t.start() # after 1 seconds, "hello, world" will be printed
from multiprocessing import Process import threading import time def foo(i): print ‘say hi‘,i for i in range(10): p = Process(target=foo,args=(i,)) p.start()
注意:由于进程之间的数据需要各自持有一份,所以创建进程需要的非常大的开销。
进程数据共享
进程各自持有一份数据,默认无法共享数据
#!/usr/bin/env python #coding:utf-8 from multiprocessing import Process from multiprocessing import Manager import time li = [] def foo(i): li.append(i) print ‘say hi‘,li for i in range(10): p = Process(target=foo,args=(i,)) p.start() print ‘ending‘,li
#方法一,Array from multiprocessing import Process,Array temp = Array(‘i‘, [11,22,33,44]) def Foo(i): temp[i] = 100+i for item in temp: print i,‘----->‘,item for i in range(2): p = Process(target=Foo,args=(i,)) p.start() #方法二:manage.dict()共享数据 from multiprocessing import Process,Manager manage = Manager() dic = manage.dict() def Foo(i): dic[i] = 100+i print dic.values() for i in range(2): p = Process(target=Foo,args=(i,)) p.start() p.join()
‘c‘: ctypes.c_char, ‘u‘: ctypes.c_wchar, ‘b‘: ctypes.c_byte, ‘B‘: ctypes.c_ubyte, ‘h‘: ctypes.c_short, ‘H‘: ctypes.c_ushort, ‘i‘: ctypes.c_int, ‘I‘: ctypes.c_uint, ‘l‘: ctypes.c_long, ‘L‘: ctypes.c_ulong, ‘f‘: ctypes.c_float, ‘d‘: ctypes.c_double
from multiprocessing import Process, Queue def f(i,q): print(i,q.get()) if __name__ == ‘__main__‘: q = Queue() q.put("h1") q.put("h2") q.put("h3") for i in range(10): p = Process(target=f, args=(i,q,)) p.start()
当创建进程时(非使用时),共享数据会被拿到子进程中,当进程中执行完毕后,再赋值给原值。
#!/usr/bin/env python # -*- coding:utf-8 -*- from multiprocessing import Process, Array, RLock def Foo(lock,temp,i): """ 将第0个数加100 """ lock.acquire() temp[0] = 100+i for item in temp: print i,‘----->‘,item lock.release() lock = RLock() temp = Array(‘i‘, [11, 22, 33, 44]) for i in range(20): p = Process(target=Foo,args=(lock,temp,i,)) p.start()
进程池
进程池内部维护一个进程序列,当使用时,则去进程池中获取一个进程,如果进程池序列中没有可供使用的进进程,那么程序就会等待,直到进程池中有可用进程为止。
进程池中有两个方法:
#!/usr/bin/env python # -*- coding:utf-8 -*- from multiprocessing import Process,Pool import time def Foo(i): time.sleep(2) return i+100 def Bar(arg): print arg pool = Pool(5) #print pool.apply(Foo,(1,)) #print pool.apply_async(func =Foo, args=(1,)).get() for i in range(10): pool.apply_async(func=Foo, args=(i,),callback=Bar) print ‘end‘ pool.close() pool.join()#进程池中进程执行完毕后再关闭,如果注释,那么程序直接关闭。
线程和进程的操作是由程序触发系统接口,最后的执行者是系统;协程的操作则是程序员。
协程存在的意义:对于多线程应用,CPU通过切片的方式来切换线程间的执行,线程切换时需要耗时(保存状态,下次继续)。协程,则只使用一个线程,在一个线程中规定某个代码块执行顺序。
协程的适用场景:当程序中存在大量不需要CPU的操作时(IO),适用于协程;
greenlet
#!/usr/bin/env python # -*- coding:utf-8 -*- from greenlet import greenlet def test1(): print 12 gr2.switch() print 34 gr2.switch() def test2(): print 56 gr1.switch() print 78 gr1 = greenlet(test1) gr2 = greenlet(test2) gr1.switch()
import gevent def foo(): print(‘Running in foo‘) gevent.sleep(0) print(‘Explicit context switch to foo again‘) def bar(): print(‘Explicit context to bar‘) gevent.sleep(0) print(‘Implicit context switch back to bar‘) gevent.joinall([ gevent.spawn(foo), gevent.spawn(bar), ])
遇到IO操作自动切换:
from gevent import monkey; monkey.patch_all() import gevent import urllib2 def f(url): print(‘GET: %s‘ % url) resp = urllib2.urlopen(url) data = resp.read() print(‘%d bytes received from %s.‘ % (len(data), url)) gevent.joinall([ gevent.spawn(f, ‘https://www.python.org/‘), gevent.spawn(f, ‘https://www.yahoo.com/‘), gevent.spawn(f, ‘https://github.com/‘), ])
标签:opened 进程池 urllib2 工作 大量 序列 log exe running
原文地址:http://www.cnblogs.com/shizhengwen/p/6574870.html