'''Created on 2017-2-27 @author: xiaoye'''#coding: utf-8import threadimport timefrom subPRocess import Popen,PIPE def scan_ip(ip): process = Popen('ping -c 2 ' + ip, stdin=PIPE, stdout=PIPE, shell=True) data = process.stdout.read() if 'ttl' in data: print '%s is live ,now time is %s' % (ip, time.strftime('%H:%M:%S')) if __name__ == '__main__': #scan_ip('111.13.147.229') ips = raw_input() ip_header = '.'.join(ips.split('.')[:3]) for i in range(1,255): ip = ip_header + '.' + str(i) #print ip thread.start_new_thread(scan_ip, (ip,)) time.sleep(0.1)运行情况：速度还行，稳定性一般thread模块，核心在：
thread.start_new_thread(scan_ip, (ip,)) time.sleep(0.1)scan_ip是要执行的函数，(ip,)是传入的参数，记得sleep一下2.threading模块用法：demo:'''Created on 2017-2-28@author: xiaoye'''#coding: utf-8import threadingimport time def test(th): print 'i am doing %s %s' % (th, time.strftime('%H:%M:%S')) def main(): thread = [] keys = ['movie_th','swim_th','listen_th','learn_th','movie_th','swim_th','listen_th','learn_th','movie_th','swim_th','listen_th','learn_th','movie_th','swim_th','listen_th','learn_th'] thread_count = len(keys) #print thread_count for i in range(thread_count): t = threading.Thread(target=test, args=(keys[i],)) thread.append(t) for i in range(thread_count): thread[i].start() for i in range(thread_count): thread[i].join() if __name__ == '__main__': main()运行情况：可以看到，基本是同时运行的，threading.Thread模块的一种用法就是这样：
for i in range(thread_count): t = threading.Thread(target=test, args=(keys[i],)) thread.append(t) for i in range(thread_count): thread[i].start() for i in range(thread_count): thread[i].join()模式1.：一个列表存放所有线程，start()执行列表中线程，join()等待运行完毕模式1？，还有模式2吗？当然，模式2就是从threading.Thread继承一个子类class，重写父类run方法，实现多线程运行run函数，而这种也是非常良好的写法demo:# -*- coding: utf-8 -*-import threading class T(threading.Thread): def __init__(self): threading.Thread.__init__(self) def run(self): #继承,threading.Thread子类, 重写run方法, run方法在start()后自动执行 print 'i love you' def main(): thread = [] for i in range(10): thread.append(T()) for i in thread: i.start() for i in thread: i.join() if __name__ == '__main__': main()运行情况：二、线程间的数据守护Queue绝对是保护线程间数据安全的好选择，有关于Queue，大家可以自行百度其用法，我发出一点经常用的：Queue.qsize() 返回队列的大小Queue.empty() 如果队列为空，返回True,反之FalseQueue.full() 如果队列满了，返回True,反之FalseQueue.full 与 maxsize 大小对应Queue.get([block[, timeout]]) 获取队列，timeout等待时间Queue.get_nowait() 相当Queue.get(False)非阻塞 Queue.put(item) 写入队列，timeout等待时间Queue.put_nowait(item) 相当Queue.put(item, False) Queue.task_done() 在完成一项工作之后，Queue.task_done() 函数向任务已经完成的队列发送一个信号Queue.join() 实际上意味着等到队列为空，再执行别的操作三、多线程threading.Thread+Queue实现渗透测试工具编写脚本放出来：1.多线程c段存活主机扫描：
'''Created on 2017-2-28@author: xiaoye'''#coding: utf-8import timeimport sysimport threadingimport Queuefrom subprocess import Popen,PIPE class Quethread(threading.Thread): def __init__(self, que): threading.Thread.__init__(self) self._que = que def run(self): while not self._que.empty(): ip = self._que.get() process = Popen('ping -c 2 ' + ip, stdin=PIPE, stdout=PIPE, shell=True) data = process.stdout.read() if 'ttl' in data: sys.stdout.write('%s is live %s/n' % (ip, time.strftime('%H:%M:%S'))) def main(): que = Queue.Queue() ips = raw_input() thread = [] thread_count = 200 ip_head = '.'.join(ips.split('.')[:3]) #print ip_head for i in range(1, 255): que.put(ip_head + '.' + str(i)) '''for i in range(1,255): print que.get()''' for i in range(thread_count): thread.append(Quethread(que)) for i in thread: i.start() for i in thread: i.join() if __name__ == '__main__': main()Ubuntu下运行成功，win下需要修改Popen里的命令等，截图：速度很快，稳定性较强c段主机存活脚本：https://github.com/xiaoyecent/ping_threading_Queue2.py版多线程御剑--目录扫描--支持自定义字典、输出文件位置以及自定义线程数：
'''@author: xiaoye'''#coding: utf-8import requestsimport sysimport threading#import timeimport Queuefrom optparse import OptionParser reload(sys)sys.setdefaultencoding('utf8') class Doscan(threading.Thread): def __init__(self, que): threading.Thread.__init__(self) self._que = que def run(self): while not self._que.empty(): d = self._que.get() try: r = requests.get(url + d, headers=headers, timeout=3) sys.stdout.write(d + ' is scan status:' + str(r.status_code) + '/n') if r.status_code == 200: with open(option.outfile, 'a') as f: f.write(url + d + '/n') except: pass def main(): thread = [] thread_count = option.threadcount que = Queue.Queue() with open(option.dictname, 'r') as f: for d in f.readlines(): d = d.strip('/n') que.put(d) for i in range(thread_count): thread.append(Doscan(que)) for i in thread: i.start() for i in thread: i.join() if __name__ == '__main__': parse = OptionParser() parse.add_option('-u', '--url', dest='input_url', type='string', help='the url you wan to scan dir') parse.add_option('-o', '--out', dest='outfile', type='string', help='output filename', default='result.txt') parse.add_option('-s', '--speed', dest='threadcount', type='int', default=60, help='the thread_count') parse.add_option('-d', '--dict', dest='dictname', type='string', help='dict filename') (option, args) = parse.parse_args() headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64; rv:50.0) Gecko/20100101 Firefox/50.0'} url = option.input_url main()Usage: scan_dir.py [options] Options: -h, --help show this help message and exit -u INPUT_URL, --url=INPUT_URL the url you wan to scan dir -o OUTFILE, --out=OUTFILE output filename -s THREADCOUNT, --speed=THREADCOUNT the thread_count -d DICTNAME, --dict=DICTNAME dict filename参数用法贴出来运行情况举个例子：-u http://localhost -s 30 -d d://php.txt -o d://ichunqiu.txt：结果：
运行速度取决于线程数（默认60）和实际环境源码：https://github.com/xiaoyecent/scan_dir四、总结多线程加队列实现线程间的数据保护是很好的搭配，threading.Thread+Queue的用法希望大家能够掌握，另外，继承threading.Thread写出子类，重写父类run方法来实现多线程的写法也值得借鉴
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