python 之并发编程更新版进程池与进程池比较与回调函数

一.更新版进程池与进程池比较

 

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

def func(i):
    print('Process', i, os.getpid())
    time.sleep(0.1)
    print("Process..end")
    return 88899

 

# (1)ProcessPoolExcutor 进程池的基本使用(改良版)

相对于旧版的进程池,

一定会等待子进程全部执行完毕之后,再终止程序,相当于过去的Process流程

shutdown 相当于Process里面的join

 

if __name__ == "__main__":
    # (1)ProcessPoolExecutor() <==> Pool()
    p = ProcessPoolExecutor(5)
    # (2)submit() <==> apply_async()
    res = p.submit(func, 55)
    # (3)result() <==> get()
    res = res.result()
    print(res) #
    # (4)shutdown <==> close + join
    #p.shutdown()
    print("主进程执行结束...")

View Code

 

# (2)线程池

 

from threading import current_thread as ct
def func(i):
    print("thread",i,ct().ident)
    time.sleep(0.1)
    print("thread %s end" % (i))

#可以在参数中指定并发的线程数
tp = ThreadPoolExecutor(10)
for i in range(20):
    tp.submit(func,i)
#tp.shutdown()
print("主线程执行结束...")

View Code

 

# (3)线程池的返回值

 

from threading import current_thread as cthread

def func(i):
    print("thread", i, cthread().ident)
    # 加延迟防止个别线程因为执行速度过快,又接收任务,阻碍新线程的创建
    # time.sleep(0.1)
    print("threading %s end" % (i))
    # return "*" * i
    return cthread().ident


tp = ThreadPoolExecutor()
lst = []
setvar = set()
for i in range(10):
    res = tp.submit(func,i)
    lst.append(res)

for i in lst:
    # print(i.result())
    setvar.add(i.result())
print(setvar,len(setvar))
print("主线程执行结束...")

View Code

 

# (4)map 返回迭代器

 

from threading import current_thread as cthread
def func(i):
    print("threading",i,cthread().ident)
    time.sleep(0.1)
    print("thread %s end" % (i))
    return "*" * i

tp = ThreadPoolExecutor(5)
it = tp.map(func,range(20)) # map
from collections import Iterable,Iterator
print(isinstance(it,Iterator))
for i in it:
    print(i)

tp.shutdown()
print("主线程执行结束..")

View Code

 

二.回调函数

回调函数:

    把函数当成参数传递的另外一个函数

    函数先执行,最后在执行当参数传递的这个函数,整个过程是回调,这个参数是回调函数

 

# (1) 线程池的回调函数是由 子线程完成

 

from concurrent.futures import  ThreadPoolExecutor
from threading import current_thread as cthread

import time
def func(i):
    print("thread",i,cthread().ident)
    time.sleep(0.1)
    print("thread %s end" % (i))
    return "*" * i

# 定义成回调函数
def call_back(args):
    print("call back:",cthread().ident)
    print(args.result())

tp = ThreadPoolExecutor(5)
for i in range(1,11):
    # submit(函数,参数).add_done_callback(要添加的回调函数)
    tp.submit(func,i).add_done_callback(call_back)
    
tp.shutdown()
print("主线程:",cthread().ident)

View Code

 

# (2) 进程池的回调函数是由 主进程完成

 

from concurrent.futures import ProcessPoolExecutor
import os,time
def func(i):
    print("Process",i,os.getpid())
    time.sleep(0.1)
    print("Process %s end" % (i))

if __name__ == "__main__":
    p = ProcessPoolExecutor(5)
    p.submit(func,11)
    p.shutdown()
    print("主进程:",os.getpid())

View Code

 

例2：

from concurrent.futures import ProcessPoolExecutor
import os,time
def func(i):
    print("Process",i,os.getpid())
    time.sleep(0.1)
    print("Process %s end" % (i))
    return i * "*"

# 回调函数
def call_back(args):
    print("call back:",os.getpid())
    # print(args)
    print(args.result())

if __name__ == "__main__":
    # 同一时间最多允许5个进程并发
    tp = ProcessPoolExecutor(5)
    for i in range(1,11):
        tp.submit(func,i).add_done_callback(call_back)
    tp.shutdown()
    print("主进程id:",os.getpid())

View Code

 

标签：__,python,tp,更新版,print,func,time,进程,import
来源： https://www.cnblogs.com/hszstudypy/p/11294622.html