python 线程池ThreadPoolExecutor操作测试

先贴上代码：

#coding:utf-8
from concurrent.futures import ThreadPoolExecutor,as_completed
import requests
import time

def getHtmllen(url):
    res =  requests.get(url).text
    mlen =len(res)
    return  url,mlen
def start():
    urls = []
    for i in range(435194,435194-20,-1):
        url='http://****/archives/%d.html' % i
        urls.append(url)
    start =time.time()
    '''
    with ThreadPoolExecutor() as pool:
        results = pool.map(getHtmllen,urls)
        for result in results:
            print (result)
    end = time.time()
    print ('cost time is :',end -start)
    '''
    with ThreadPoolExecutor() as pool:
        futures = [pool.submit(getHtmllen, url) for url in urls]
        for future in futures:
            print(future.result())
        #for future in as_completed(futures):
            #print (future.result())
    end = time.time()
    print ("cost times is :",end-start)

def main():
    start()
if __name__ == '__main__':
    main()

其中涉及到2种方式进行线程池操作：

1、

    with ThreadPoolExecutor() as pool:
        results = pool.map(getHtmllen,urls)
        for result in results:
            print (result)

2、

    with ThreadPoolExecutor() as pool:
        futures = [pool.submit(getHtmllen, url) for url in urls]
        for future in futures:
            print(future.result())
        #for future in as_completed(futures):
            #print (future.result())

第二种中，有2种方式展示结果，分别为：

按照顺序打印：

for future in futures:
            print(future.result())

乱序打印：

 #for future in as_completed(futures):
            #print (future.result())

注：1、使用map函数，简单；2、future模式更强大