【python】进程与线程

from multiprocessing import Process
import os

# 子进程要执行的代码
def run_proc(name):
    print(‘Run child process %s (%s)...‘ % (name, os.getpid()))

if __name__==‘__main__‘:
    print(‘Parent process %s.‘ % os.getpid())
    p = Process(target=run_proc, args=(‘test‘,))
    print(‘Child process will start.‘)
    p.start()
    p.join()
    print(‘Child process end.‘)

from multiprocessing import Pool
import os, time, random

def long_time_task(name):
    print(‘Run task %s (%s)...‘ % (name, os.getpid()))
    start = time.time()
    time.sleep(random.random() * 3)
    end = time.time()
    print(‘Task %s runs %0.2f seconds.‘ % (name, (end - start)))

if __name__==‘__main__‘:
    print(‘Parent process %s.‘ % os.getpid())
    p = Pool(4)
    for i in range(5):
        p.apply_async(long_time_task, args=(i,))
    print(‘Waiting for all subprocesses done...‘)
    p.close()
    p.join()
    print(‘All subprocesses done.‘)

import subprocess

print(‘$ nslookup www.python.org‘)
r = subprocess.call([‘nslookup‘,‘www.python.org‘])
print(‘Exit code:‘,r)

import subprocess

print(‘$ nslookup‘)
p=subprocess.Popen([‘nslookup‘],stdin=subprocess.PIPE,stdout=subprocess.PIPE,stderr=subprocess.PIPE)
output,err=p.communicate(b‘set q=mx\npython.org\nexit\n‘)
print(output.decode(‘utf-8‘))
print(‘Exit code:‘,p.returncode)

from multiprocessing import Process,Queue
import os,time,random

def write(q):
    print(‘Process to write: %s‘ % os.getpid())
    for value in[‘A‘,‘B‘,‘C‘]:
        print(‘Put %s to queue...‘ % value)
        q.put(value)
        time.sleep(random.random())
        
def read(q):
    print(‘Process to read: %s‘ % os.getpid())
    while True:
        value = q.get(True)
        print(‘Get %s from queue.‘ % value)
        
if __name__==‘__main__‘:
    q=Queue()
    pw=Process(target=write,args=(q,))
    pr=Process(target=read,args=(q,))
    pw.start()
    pr.start()
    pw.join()
    pr.terminate()

import time,threading

def loop():
    print(‘thread %s is running...‘ % threading.current_thread().name)
    n=0
    while n<5:
        n=n+1
        print(‘thread %s >>> %s‘ % (threading.current_thread().name,n))
        time.sleep(1)
    print(‘thread %s ended.‘ % threading.current_thread().name)
    
print(‘thread %s is running...‘ % threading.current_thread().name)
t = threading.Thread(target=loop,name=‘LoopThread‘)
t.start()
t.join()
print(‘thread %s ended.‘ % threading.current_thread().name)

import time,threading

blance=0
lock=threading.Lock()

def run_thread(n):
    for i in range(100000):
        lock.acquire()
        try:
            change_it(n)
        finally:
            lock.release()

import threading,multiprocessing

def loop():
    x=0
    while True:
        x = x^1

for i in range(multiprocessing.cpu_count()):
    t = threading.Thread(target=loop)
    t.start()

import threading

local_school=threading.local

def process_student():
    std = local_school.student
    print(‘Hello,%s (in %s)‘ % (std,threading.current_thread().name))
    
def process_thread(name):
    local_school.student=name
    process_student()

t1=threading.Thread(target=process_thread,args=(‘Alice‘,),name=‘Thread-A‘)
t2=threading.Thread(target=process_thread,args=(‘Bob‘,),name=‘Thread-B‘)
t1.start()
t2.start()
t1.join()
t2.join()

# task_master.py

import random, time, queue
from multiprocessing.managers import BaseManager

# 发送任务的队列:
task_queue = queue.Queue()
# 接收结果的队列:
result_queue = queue.Queue()

# 从BaseManager继承的QueueManager:
class QueueManager(BaseManager):
    pass

# 把两个Queue都注册到网络上, callable参数关联了Queue对象:
QueueManager.register(‘get_task_queue‘, callable=lambda: task_queue)
QueueManager.register(‘get_result_queue‘, callable=lambda: result_queue)
# 绑定端口5000, 设置验证码‘abc‘:
manager = QueueManager(address=(‘‘, 5000), authkey=b‘abc‘)
# 启动Queue:
manager.start()
# 获得通过网络访问的Queue对象:
task = manager.get_task_queue()
result = manager.get_result_queue()
# 放几个任务进去:
for i in range(10):
    n = random.randint(0, 10000)
    print(‘Put task %d...‘ % n)
    task.put(n)
# 从result队列读取结果:
print(‘Try get results...‘)
for i in range(10):
    r = result.get(timeout=10)
    print(‘Result: %s‘ % r)
# 关闭:
manager.shutdown()
print(‘master exit.‘)

# task_worker.py

import time, sys, queue
from multiprocessing.managers import BaseManager

# 创建类似的QueueManager:
class QueueManager(BaseManager):
    pass

# 由于这个QueueManager只从网络上获取Queue，所以注册时只提供名字:
QueueManager.register(‘get_task_queue‘)
QueueManager.register(‘get_result_queue‘)

# 连接到服务器，也就是运行task_master.py的机器:
server_addr = ‘127.0.0.1‘
print(‘Connect to server %s...‘ % server_addr)
# 端口和验证码注意保持与task_master.py设置的完全一致:
m = QueueManager(address=(server_addr, 5000), authkey=b‘abc‘)
# 从网络连接:
m.connect()
# 获取Queue的对象:
task = m.get_task_queue()
result = m.get_result_queue()
# 从task队列取任务,并把结果写入result队列:
for i in range(10):
    try:
        n = task.get(timeout=1)
        print(‘run task %d * %d...‘ % (n, n))
        r = ‘%d * %d = %d‘ % (n, n, n*n)
        time.sleep(1)
        result.put(r)
    except Queue.Empty:
        print(‘task queue is empty.‘)
# 处理结束:
print(‘worker exit.‘)