python基础-进程池、submit同异步调用、shutdown参数、ProcessPoolExecutor进程池、进程池ftp

引入进程池

在学习线程池之前，我们先看一个例子

from multiprocessing import  Process
import  time
def task(name):
    print("name",name)
    time.sleep(1)

if __name__ == "__main__":
    start = time.time()
    p1 = Process(target=task,args=("safly1",))
    p2 = Process(target=task, args=("safly2",))
    p3 = Process(target=task, args=("safly3",))

    p1.start()
    p2.start()
    p3.start()

    p1.join()
    p2.join()
    p3.join()

    print("main")

    end = time.time()
    print(end- start)

输出如下：

name safly1
name safly2
name safly3
main
1.2071197032928467

以上的方式是一个个创建进程，这样的耗费时间才1秒多，虽然高效，但是有什么弊端呢？
如果并发很大的话，会给服务器带来很大的压力，所以引入了进程池的概念

使用ProcessPoolExecutor进程池

Python3.2开始，标准库为我们提供了concurrent.futures模块，它提供了ThreadPoolExecutor和ProcessPoolExecutor两个类，实现了对threading和multiprocessing的进一步抽象，对编写线程池/进程池提供了直接的支持。

通过ProcessPoolExecutor 来做示例。
我们来看一个最简单的进程池

from concurrent.futures import ProcessPoolExecutor
import  time
def task(name):
    print("name",name)
    time.sleep(1)

if __name__ == "__main__":
    start = time.time()
    ex = ProcessPoolExecutor(2)

    for i in range(5):
        ex.submit(task,"safly%d"%i)
    ex.shutdown(wait=True)

    print("main")
    end = time.time()
    print(end - start)

输出如下：

E:\python\python_sdk\python.exe "E:/python/py_pro/4 进程池.py"
name safly0
name safly1
name safly2
name safly3
name safly4
main
3.212218999862671

简单解释下：
ProcessPoolExecutor（2）创建一个进程池，容量为2，循环submit出5个进程，然后就在线程池队列里面，执行多个进程，ex.shutdown(wait=True)意思是进程都执行完毕，在执行主进程的内容

使用shutdown

ex.shutdown(wait=True)是进程池内部的进程都执行完毕，才会关闭，然后执行后续代码
如果改成false呢？看如下代码

from concurrent.futures import ProcessPoolExecutor
import  time
def task(name):
    print("name",name)
    time.sleep(1)

if __name__ == "__main__":
    start = time.time()
    ex = ProcessPoolExecutor(2)

    for i in range(5):
        ex.submit(task,"safly%d"%i)
    ex.shutdown(wait=False)

    print("main")
    end = time.time()
    print(end - start)

输出如下：

main
0.01500844955444336
name safly0
name safly1
name safly2
name safly3
name safly4

使用submit同步调用

同步调用：提交/调用一个任务，然后就在原地等着，等到该任务执行完毕拿到结果，再执行下一行代码

from concurrent.futures import ProcessPoolExecutor
import time, random, os

def piao(name, n):
    print('%s is piaoing %s' % (name, os.getpid()))
    time.sleep(1)
    return n ** 2


if __name__ == '__main__':
    p = ProcessPoolExecutor(2)
    start = time.time()
    for i in range(5):
        res=p.submit(piao,'safly %s' %i,i).result() #同步调用
        print(res)

    p.shutdown(wait=True)
    print('主', os.getpid())

    stop = time.time()
    print(stop - start)

输出如下：

E:\python\python_sdk\python.exe "E:/python/py_pro/4 进程池.py"
safly 0 is piaoing 12996
0
safly 1 is piaoing 14044
1
safly 2 is piaoing 12996
4
safly 3 is piaoing 14044
9
safly 4 is piaoing 12996
16
主 12932
5.202786684036255

Process finished with exit code 0

使用submit异步调用

异步调用: 提交/调用一个任务，不在原地等着，直接执行下一行代码

# from multiprocessing import Process,Pool
from concurrent.futures import ProcessPoolExecutor
import time, random, os

def piao(name, n):
    print('%s is piaoing %s' % (name, os.getpid()))
    time.sleep(1)
    return n ** 2


if __name__ == '__main__':
    p = ProcessPoolExecutor(2)
    objs = []
    start = time.time()
    for i in range(5):
        obj = p.submit(piao, 'safly %s' % i, i)  # 异步调用
        objs.append(obj)

    p.shutdown(wait=True)
    print('主', os.getpid())
    for obj in objs:
        print(obj.result())

    stop = time.time()
    print(stop - start)

输出如下：

E:\python\python_sdk\python.exe "E:/python/py_pro/4 进程池.py"
safly 0 is piaoing 1548
safly 1 is piaoing 7872

safly 2 is piaoing 1548
safly 3 is piaoing 7872


safly 4 is piaoing 1548


主 7808
0
1
4
9
16
3.202626943588257

输出信息的换行是我标识有输出停顿的
简单说下执行流程：
由于进程池容量是容纳2个进程，所以会2+2+1 三次进入线程池执行，花费3秒

如果我们改下上面的代码，修改的代码如下：

from concurrent.futures import ProcessPoolExecutor
import time, random, os

def piao(name, n):
    print('%s is piaoing %s' % (name, os.getpid()))
    time.sleep(1)
    return n ** 2


if __name__ == '__main__':
    p = ProcessPoolExecutor(2)
    objs = []
    start = time.time()
    for i in range(5):
        obj = p.submit(piao, 'safly %s' % i, i)  # 异步调用
        objs.append(obj)

    for obj in objs:
        print(obj.result())


    p.shutdown(wait=True)
    print('主', os.getpid())


    stop = time.time()
    print(stop - start)

输出如下：（同样我用换行，标识出输出的时间段了）

E:\python\python_sdk\python.exe "E:/python/py_pro/4 进程池.py"
safly 0 is piaoing 7852
safly 1 is piaoing 8484


safly 2 is piaoing 7852
0
safly 3 is piaoing 8484
1



safly 4 is piaoing 7852
4
9


16
主 6816
3.178352117538452

进程池实现ftp

服务端：

from socket import *
from concurrent.futures import ProcessPoolExecutor
import os

server=socket(AF_INET,SOCK_STREAM)
server.setsockopt(SOL_SOCKET,SO_REUSEADDR,1)
server.bind(('127.0.0.1',8080))
server.listen(5)

def talk(conn,client_addr):
    print('进程pid: %s' %os.getpid())
    while True:
        try:
            msg=conn.recv(1024)
            if not msg:break
            conn.send(msg.upper())
        except Exception:
            break

if __name__ == '__main__':
    p=ProcessPoolExecutor(5)
    while True:
        conn,client_addr=server.accept()
        p.submit(talk,conn,client_addr)

客户端：

from socket import *

client=socket(AF_INET,SOCK_STREAM)
client.connect(('127.0.0.1',8080))


while True:
    msg=input('>>: ').strip()
    if not msg:continue

    client.send(msg.encode('utf-8'))
    msg=client.recv(1024)
    print(msg.decode('utf-8'))