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本文实例讲述了Python mutiprocessing多线程池pool操作。分享给大家供大家参考，具体如下：
python — mutiprocessing 多线程 pool
脚本代码：
root@72132server:~/python/multiprocess# ls
multiprocess_pool.py multprocess.py
root@72132server:~/python/multiprocess# cat multiprocess_pool.py
#!/usr/bin/python
# --*-- coding:utf-8 --*--
import multiprocessing
import sys,os,time
result = []#把运行的进程池放入，空的列表
def run(msg):#定义正在处理进程编号数的函数功能
print 'threading number:%s %s' %(msg,os.getpid())#打印正在处理的进程编号数与对应的系统进程号
time.sleep(2)
p = multiprocessing.Pool(processes = 25)#绑定事例，同时执行25个线程
for i in range(100):
result.append(p.apply_async(run,('%s' %i,)))#异步传输正在运行的进程数字号码
p.close()#关闭正在运行的25个进程
#p.join()
for res in result:#获取运行结果
res.get(timeout=5)
root@72132server:~/python/multiprocess#
运行情况：
1）脚本运行
root@72132server:~/python/multiprocess# python multiprocess_pool.py threading number:0 27912 threading number:1 27915 threading number:2 27913 threading number:3 27916 threading number:4 27917 threading number:5 27918 threading number:6 27919 threading number:7 27920 threading number:8 27922 threading number:9 27923 threading number:10 27924 threading number:11 27925 threading number:12 27926 threading number:13 27927 threading number:14 27928 threading number:15 27914 threading number:16 27929 threading number:17 27921 threading number:18 27930 threading number:19 27931 threading number:20 27932 threading number:21 27934 threading number:22 27935 threading number:23 27936 threading number:24 27933 threading number:25 27912 threading number:26 27915 threading number:27 27917 threading number:28 27918 threading number:29 27916 threading number:30 27913 threading number:31 27922 threading number:32 27919 threading number:33 27920 threading number:34 27923 threading number:35 27924 threading number:36 27925 threading number:37 27927 threading number:38 27921 threading number:39 27930 threading number:40 27932 threading number:41 27934 threading number:42 27935 threading number:43 27926 threading number:44 27931 threading number:45 27928 threading number:46 27929 threading number:47 27914 threading number:48 27933 threading number:49 27936 threading number:50 27912 threading number:51 27915
2）进程查看（25个进程同时运行）
root@72132server:~/python/multiprocess# ps -ef | grep multi root 27905 23930 0 22:39 pts/3 00:00:00 grep multi root@72132server:~/python/multiprocess# ps -ef | grep multi root 27911 20609 1 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27912 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27913 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27914 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27915 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27916 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27917 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27918 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27919 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27920 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27921 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27922 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27923 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27924 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27925 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27926 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27927 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27928 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27929 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27930 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27931 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27932 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27933 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27934 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27935 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27936 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27941 23930 0 22:39 pts/3 00:00:00 grep multi root@72132server:~/python/multiprocess# ps -ef | grep multi root 27911 20609 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27912 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27913 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27914 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27915 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27916 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27917 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27918 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27919 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27920 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27921 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27922 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27923 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27924 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27925 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27926 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27927 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27928 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27929 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27930 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27931 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27932 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27933 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27934 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27935 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27936 27911 0 22:39 pts/1 00:00:00 python multiprocess_pool.py root 27943 23930 0 22:39 pts/3 00:00:00 grep multi root@72132server:~/python/multiprocess#
希望本文所述对大家Python程序设计有所帮助。
本文Python mutiprocessing多线程池pool操作示例到此结束。就算偶尔难过，也要面带微笑的向着充满阳光的方向前行。小编再次感谢大家对我们的支持！