并发多线程测试

def Producer():
    urls = [
        'http://www.python.org',
        'https://segmentfault.com/a/1190000000382873',
        'http://ddt.8888play.com/news_3935.html',
        'http://douban.fm/',
        'http://docs.jinkan.org/docs/celery/getting-started/introduction.html',
        'http://formspree.io/account',
        'http://46.101.85.29/index/#/mz/multipletextsearch/',
        'https://pandao.github.io/editor.md/',
        'https://www.zhihu.com/question/21343711',
        'https://docs.python.org/3/library/queue.html',
        'http://www.python.org',
        'http://www.python.org',
    ]
    queues = queue.Queue()
    pool_size=int(multiprocessing.cpu_count()*0.5)
    print('线程池线程数量：'+str(pool_size))
    worker_threads = build_worker_pool(queues, pool_size)
    start_time = time.time()
    results = []
    for url in urls:
        queues.put(url)
    for worker in worker_threads:
        queues.put('quit')
    for worker in worker_threads:
        worker.join()

    print('Done! Time taken:{}'.format(time.time() - start_time))


def build_worker_pool(queues, size):
    workers = []
    for _ in range(size):
        worker = Consumer(queues)
        worker.start()
        workers.append(worker)
    return workers

if __name__ == '__main__':
    Producer()

import multiprocessing
urls = [
    'http://www.python.org',
    'https://segmentfault.com/a/1190000000382873',
    'http://ddt.8888play.com/news_3935.html',
    'http://douban.fm/',
    'http://docs.jinkan.org/docs/celery/getting-started/introduction.html',
    'http://formspree.io/account',
    'http://46.101.85.29/index/#/mz/multipletextsearch/',
    'https://pandao.github.io/editor.md/',
    'https://www.zhihu.com/question/21343711',
    'https://docs.python.org/3/library/queue.html',
    'http://www.python.org',
    'http://www.python.org',
]

results = []

# starttime = time.time()
# pool = TreadPool(4)  # 根据核数进行设置
# results = pool.map(urllib.request.urlopen, urls)
# print('4pool:' + str(time.time() - starttime))

# starttime = time.time()
# pool = TreadPool(8)  # 根据核数进行设置
# results = pool.map(urllib.request.urlopen, urls)
# print('8pool:' + str(time.time() - starttime))

starttime = time.time()
pool_size=multiprocessing.cpu_count()*2
pool = TreadPool(pool_size)  # 根据核数进行设置
results.append(pool.map_async(urllib.request.urlopen, urls))
print('16pool:' + str(time.time() - starttime))


pool.close()
pool.join()
for i in results:
    print (i.get())