我将如何使用concurrent.futures和队列进行实时场景？

使用Python 3的concurrent.futures模块进行并行工作相当容易,如下所示.

with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
    future_to = {executor.submit(do_work, input, 60): input for input in dictionary}
    for future in concurrent.futures.as_completed(future_to):
        data = future.result()  

将项目插入和检索到队列中也非常方便.

q = queue.Queue()
for task in tasks:
q.put(task)
while not q.empty():
   q.get()

我有一个在后台运行的脚本,用于监听更新.现在,理论上假设,当这些更新到达时,我会将它们排队并使用它们同时处理它们ThreadPoolExecutor.

现在,单独地说,所有这些组件都是孤立的,并且有意义,但我如何一起使用它们呢？我不知道是否可以ThreadPoolExecutor实时从队列中提取工作,除非预先确定的数据是什么？

简而言之,我想做的就是,每秒接收4条消息的更新,将它们推入队列,然后让我的concurrent.futures对它们进行处理.如果我不这样做,那么我会陷入一种缓慢的顺序方法.

我们来看下面Python文档中的规范示例:

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
    future_to_url = {executor.submit(load_url, url, 60): url for url in URLS}
    for future in concurrent.futures.as_completed(future_to_url):
        url = future_to_url[future]
        try:
            data = future.result()
        except Exception as exc:
            print('%r generated an exception: %s' % (url, exc))
        else:
            print('%r page is %d bytes' % (url, len(data)))

列表URLS是固定的.是否有可能实时提供此列表并让工作人员在它们来时处理它,可能是为了管理目的从队列中进行处理？我对我的方法是否真的有可能感到困惑？

Python文档中的示例,扩展为从队列中获取其工作.需要注意的是,此代码使用concurrent.futures.wait而不是concurrent.futures.as_completed允许在等待其他工作完成时启动新工作.

import concurrent.futures
import urllib.request
import time
import queue

q = queue.Queue()

URLS = ['http://www.foxnews.com/',
        'http://www.cnn.com/',
        'http://europe.wsj.com/',
        'http://www.bbc.co.uk/',
        'http://some-made-up-domain.com/']

def feed_the_workers(spacing):
    """ Simulate outside actors sending in work to do, request each url twice """
    for url in URLS + URLS:
        time.sleep(spacing)
        q.put(url)
    return "DONE FEEDING"

def load_url(url, timeout):
    """ Retrieve a single page and report the URL and contents """
    with urllib.request.urlopen(url, timeout=timeout) as conn:
        return conn.read()

# We can use a with statement to ensure threads are cleaned up promptly
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:

    # start a future for a thread which sends work in through the queue
    future_to_url = {
        executor.submit(feed_the_workers, 0.25): 'FEEDER DONE'}

    while future_to_url:
        # check for status of the futures which are currently working
        done, not_done = concurrent.futures.wait(
            future_to_url, timeout=0.25,
            return_when=concurrent.futures.FIRST_COMPLETED)

        # if there is incoming work, start a new future
        while not q.empty():

            # fetch a url from the queue
            url = q.get()

            # Start the load operation and mark the future with its URL
            future_to_url[executor.submit(load_url, url, 60)] = url

        # process any completed futures
        for future in done:
            url = future_to_url[future]
            try:
                data = future.result()
            except Exception as exc:
                print('%r generated an exception: %s' % (url, exc))
            else:
                if url == 'FEEDER DONE':
                    print(data)
                else:
                    print('%r page is %d bytes' % (url, len(data)))

            # remove the now completed future
            del future_to_url[future]

每次取url两次输出:

'http://www.foxnews.com/' page is 67574 bytes
'http://www.cnn.com/' page is 136975 bytes
'http://www.bbc.co.uk/' page is 193780 bytes
'http://some-made-up-domain.com/' page is 896 bytes
'http://www.foxnews.com/' page is 67574 bytes
'http://www.cnn.com/' page is 136975 bytes
DONE FEEDING
'http://www.bbc.co.uk/' page is 193605 bytes
'http://some-made-up-domain.com/' page is 896 bytes
'http://europe.wsj.com/' page is 874649 bytes
'http://europe.wsj.com/' page is 874649 bytes