进程池和线程池

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

def task(name,n):
    print(‘%s%s is running‘ %(name,os.getpid()))
    time.sleep(random.randint(1,3))
    return n**2

if __name__ == ‘__main__‘:
    # print(os.cpu_count())
    p=ProcessPoolExecutor(4)
    #提交任务的两种方式:
    # 同步调用:提交完一个任务之后,就在原地等待,等待任务完完整整地运行完毕拿到结果后,再执行下一行代码,会导致任务是串行执行的
    # 异步调用:提交完一个任务之后,不在原地等待,结果???,而是直接执行下一行代码,会导致任务是并发执行的

    l=[]
    for i in range(10):
        # 同步提交
        # res=p.submit(task,‘进程pid: ‘,i).result()
        # print(res)

        # 异步提交
        future=p.submit(task,‘进程pid: ‘,i)
        l.append(future)

    p.shutdown(wait=True) #关闭进程池的入口,并且在原地等待进程池内所有任务运行完毕

    for future in l:
        print(future.result())
    print(‘主‘)

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‘‘‘
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
import time,random,os
import requests


def get(url):
    print(‘%s GET %s‘ %(os.getpid(),url))
    time.sleep(3)
    response=requests.get(url)
    if response.status_code == 200:
        res=response.text
    else:
        res=‘下载失败‘
    parse(res)

def parse(res):
    time.sleep(1)
    print(‘%s 解析结果为%s‘ %(os.getpid(),len(res)))

if __name__ == ‘__main__‘:
    urls=[
        ‘https://www.baidu.com‘,
        ‘https://www.sina.com.cn‘,
        ‘https://www.tmall.com‘,
        ‘https://www.jd.com‘,
        ‘https://www.python.org‘,
        ‘https://www.openstack.org‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,

    ]

    p=ProcessPoolExecutor(9)
    l=[]
    start=time.time()
    for url in urls:
        future=p.submit(get,url)
        l.append(future)
    p.shutdown(wait=True)


    print(‘主‘,time.time()-start)
‘‘‘


‘‘‘

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


def get(url):
    print(‘%s GET %s‘ %(os.getpid(),url))
    time.sleep(3)
    response=requests.get(url)
    if response.status_code == 200:
        res=response.text
    else:
        res=‘下载失败‘
    return res

def parse(future):
    time.sleep(1)
    res=future.result()
    print(‘%s 解析结果为%s‘ %(os.getpid(),len(res)))

if __name__ == ‘__main__‘:
    urls=[
        ‘https://www.baidu.com‘,
        ‘https://www.sina.com.cn‘,
        ‘https://www.tmall.com‘,
        ‘https://www.jd.com‘,
        ‘https://www.python.org‘,
        ‘https://www.openstack.org‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,

    ]

    p=ProcessPoolExecutor(9)

    start=time.time()
    for url in urls:
        future=p.submit(get,url)
        # 异步调用:提交完一个任务之后,不在原地等待,而是直接执行下一行代码,会导致任务是并发执行的,,结果futrue对象会在任务运行完毕后自动传给回调函数
        future.add_done_callback(parse)  #parse会在任务运行完毕后自动触发,然后接收一个参数future对象

    p.shutdown(wait=True)


    print(‘主‘,time.time()-start)
    print(‘主‘,os.getpid())
‘‘‘



from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
from threading import current_thread
import time,random,os
import requests


def get(url):
    print(‘%s GET %s‘ %(current_thread().name,url))
    time.sleep(3)
    response=requests.get(url)
    if response.status_code == 200:
        res=response.text
    else:
        res=‘下载失败‘
    return res

def parse(future):
    time.sleep(1)
    res=future.result()
    print(‘%s 解析结果为%s‘ %(current_thread().name,len(res)))

if __name__ == ‘__main__‘:
    urls=[
        ‘https://www.baidu.com‘,
        ‘https://www.sina.com.cn‘,
        ‘https://www.tmall.com‘,
        ‘https://www.jd.com‘,
        ‘https://www.python.org‘,
        ‘https://www.openstack.org‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,
        ‘https://www.baidu.com‘,

    ]

    p=ThreadPoolExecutor(4)
    start=time.time()
    for url in urls:
        future=p.submit(get,url)
        future.add_done_callback(parse)

    p.shutdown(wait=True)

    print(‘主‘,current_thread().name,time.time()-start)