Python：类似“map”的东西在线程上工作

Question

Closed. This question is seeking recommendations for software libraries, tutorials, tools, books, or other off-site resources. It does not meet Stack Overflow guidelines. It is not currently accepting answers.

---

我们不允许提出寻求软件库、教程、工具、书籍或其他场外资源推荐的问题。您可以编辑问题，以便用事实和引文来回答。

8 年前已关闭。

Answer 1

这是我的线程映射的实现：

from threading import Thread
from queue import Queue

def thread_map(f, iterable, pool=None):
    """
    Just like [f(x) for x in iterable] but each f(x) in a separate thread.
    :param f: f
    :param iterable: iterable
    :param pool: thread pool, infinite by default
    :return: list if results
    """
    res = {}
    if pool is None:
        def target(arg, num):
            try:
                res[num] = f(arg)
            except:
                res[num] = sys.exc_info()

        threads = [Thread(target=target, args=[arg, i]) for i, arg in enumerate(iterable)]
    else:
        class WorkerThread(Thread):
            def run(self):
                while True:
                    try:
                        num, arg = queue.get(block=False)
                        try:
                            res[num] = f(arg)
                        except:
                            res[num] = sys.exc_info()
                    except Empty:
                        break

        queue = Queue()
        for i, arg in enumerate(iterable):
            queue.put((i, arg))

        threads = [WorkerThread() for _ in range(pool)]

    [t.start() for t in threads]
    [t.join() for t in threads]
    return [res[i] for i in range(len(res))]

Answer 2

Python 模块Queue 可能会帮助你。使用一个线程，该线程使用 Queue.put() 将所有 url 推送到队列中，工作线程只需 get() 一一地获取 URL。

Python 文档：queue — 同步队列类

Answer 3

我将其包装在一个函数中（未经测试）：

import itertools
import threading
import urllib2
import Queue

def openurl(url, queue):
    def starter():
        try:
            result = urllib2.urlopen(url)
        except Ecxeption, exc:
            def raiser():
                raise exc
            queue.put((url, raiser))
        else:
            queue.put((url, lambda:result))
    threadind.Thread(target=starter).start()

myurls = ... # the list of urls
myqueue = Queue.Queue()

map(openurl, myurls, itertools.repeat(myqueue))

for each in myurls:
    url, getresult = queue.get()
    try:
        result = getresult()
    except Exception, exc:
        print 'exception raised:' + str(exc)
    else:
        # do stuff with result

Answer 4

multiprocessing.Pool< 中有一个 map 方法/a>.这会执行多个进程。

如果多个进程不是你的菜，你可以使用 multiprocessing.dummy< /a> 使用线程。

import urllib
import multiprocessing.dummy

p = multiprocessing.dummy.Pool(5)
def f(post):
    return urllib.urlopen('http://stackoverflow.com/questions/%u' % post)

print p.map(f, range(3329361, 3329361 + 5))

Answer 5

有人建议我为此使用 futures 包。我尝试了一下，似乎有效。

http://pypi.python.org/pypi/futures

这是一个示例：

"Download many URLs in parallel."

import functools
import urllib.request
import futures

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 load_url(url, timeout):
    return urllib.request.urlopen(url, timeout=timeout).read()

with futures.ThreadPoolExecutor(50) as executor:
   future_list = executor.run_to_futures(
           [functools.partial(load_url, url, 30) for url in URLS])