We can use a with statement to ensure threads are cleaned up promptly

with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:

# Start the load operations and mark each future with its URL
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)))</code></pre> 

從運行結果可以看出， as_completed不是按照URLS列表元素的順序返回的 。

ziwenxie :: ~ ? python example3.py
'http://example.com/' page is 1270 byte
'https://api.github.com/' page is 2039 bytes
'http://httpbin.org' page is 12150 bytes

使用map

# example4.py
import concurrent.futures
import urllib.request
URLS = ['http://httpbin.org', 'http://example.com/', 'https://api.github.com/']
def load_url(url):
    with urllib.request.urlopen(url, timeout=60) as conn:
        return conn.read()
# We can use a with statement to ensure threads are cleaned up promptly
with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
    for url, data in zip(URLS, executor.map(load_url, URLS)):
        print('%r page is %d bytes' % (url, len(data)))

從運行結果可以看出， map是按照URLS列表元素的順序返回的 ，并且寫出的代碼更加簡潔直觀，我們可以根據具體的需求任選一種。

ziwenxie :: ~ ? python example4.py
'http://httpbin.org' page is 12150 bytes
'http://example.com/' page is 1270 bytes
'https://api.github.com/' page is 2039 bytes

第三種選擇wait

wait方法接會返回一個tuple(元組)，tuple中包含兩個set(集合)，一個是completed(已完成的)另外一個是uncompleted(未完成的)。使用wait方法的一個優勢就是獲得更大的自由度，它接收三個參數FIRST_COMPLETED, FIRST_EXCEPTION 和ALL_COMPLETE，默認設置為ALL_COMPLETED。

我們通過下面這個例子來看一下三個參數的區別

from concurrent.futures import ThreadPoolExecutor, wait, as_completed
from time import sleep
from random import randint
def return_after_random_secs(num):
    sleep(randint(1, 5))
    return "Return of {}".format(num)
pool = ThreadPoolExecutor(5)
futures = []
for x in range(5):
    futures.append(pool.submit(return_after_random_secs, x))
print(wait(futures))
# print(wait(futures, timeout=None, return_when='FIRST_COMPLETED'))

如果采用默認的ALL_COMPLETED，程序會阻塞直到線程池里面的所有任務都完成。

ziwenxie :: ~ ? python example5.py
DoneAndNotDoneFutures(done={
<Future at 0x7f0b06c9bc88 state=finished returned str>,
<Future at 0x7f0b06cbaa90 state=finished returned str>,
<Future at 0x7f0b06373898 state=finished returned str>,
<Future at 0x7f0b06352ba8 state=finished returned str>,
<Future at 0x7f0b06373b00 state=finished returned str>}, not_done=set())

如果采用FIRST_COMPLETED參數，程序并不會等到線程池里面所有的任務都完成。

ziwenxie :: ~ ? python example5.py
DoneAndNotDoneFutures(done={
<Future at 0x7f84109edb00 state=finished returned str>,
<Future at 0x7f840e2e9320 state=finished returned str>,
<Future at 0x7f840f25ccc0 state=finished returned str>},
not_done={<Future at 0x7f840e2e9ba8 state=running>,
<Future at 0x7f840e2e9940 state=running>})

思考題

寫一個小程序對比multiprocessing.pool(ThreadPool)和ProcessPollExecutor(ThreadPoolExecutor)在執行效率上的差距，結合上面提到的Future思考為什么會造成這樣的結果。

來自：http://developer.51cto.com/art/201701/527525.htm