Pipe()只能有兩個(gè)端點(diǎn)。

Queue()可以有多個(gè)生產(chǎn)者和消費(fèi)者。

何時(shí)使用它們

如果您需要兩個(gè)以上的點(diǎn)進(jìn)行通信，請(qǐng)使用Queue() 。

如果你需要絕對(duì)性能， Pipe()要快得多，因?yàn)镼ueue()是建立在Pipe()之上的。

績(jī)效基準(zhǔn)

假設(shè)您想要生成兩個(gè)進(jìn)程并盡快在它們之間發(fā)送消息。 這些是使用Pipe()和Queue()類似測(cè)試之間的拖拽競(jìng)賽的時(shí)間結(jié)果......這是在運(yùn)行Ubuntu 11.10和Python 2.7.2的ThinkpadT61上。

僅供參考，我將JoinableQueue()結(jié)果作為獎(jiǎng)勵(lì)投入; JoinableQueue()在queue.task_done()時(shí)會(huì)queue.task_done()任務(wù)(它甚至不知道特定任務(wù)，它只計(jì)算隊(duì)列中未完成的任務(wù))，因此queue.join()知道工作已完成。

這個(gè)答案底部的每個(gè)代碼......

mpenning@mpenning-T61:~$ python multi_pipe.py

Sending 10000 numbers to Pipe() took 0.0369849205017 seconds

Sending 100000 numbers to Pipe() took 0.328398942947 seconds

Sending 1000000 numbers to Pipe() took 3.17266988754 seconds

mpenning@mpenning-T61:~$ python multi_queue.py

Sending 10000 numbers to Queue() took 0.105256080627 seconds

Sending 100000 numbers to Queue() took 0.980564117432 seconds

Sending 1000000 numbers to Queue() took 10.1611330509 seconds

mpnening@mpenning-T61:~$ python multi_joinablequeue.py

Sending 10000 numbers to JoinableQueue() took 0.172781944275 seconds

Sending 100000 numbers to JoinableQueue() took 1.5714070797 seconds

Sending 1000000 numbers to JoinableQueue() took 15.8527247906 seconds

mpenning@mpenning-T61:~$

總之， Pipe()比Queue()快三倍。 除非你真的必須有好處，否則不要考慮JoinableQueue() 。

獎(jiǎng)金材料2

多處理引入了信息流的細(xì)微變化，除非您知道一些快捷方式，否則會(huì)使調(diào)試變得困難。 例如，在許多條件下通過(guò)字典索引時(shí)，您可能有一個(gè)可正常工作的腳本，但在某些輸入中很少失敗。

通常我們會(huì)在整個(gè)python進(jìn)程崩潰時(shí)找到失敗的線索; 但是，如果多處理功能崩潰，則不會(huì)將未經(jīng)請(qǐng)求的崩潰回溯打印到控制臺(tái)。 追蹤未知的多處理崩潰是很困難的，沒(méi)有一個(gè)線索來(lái)解決崩潰的過(guò)程。

我發(fā)現(xiàn)追蹤多處理崩潰信息的最簡(jiǎn)單方法是將整個(gè)多處理函數(shù)包裝在try / except并使用traceback.print_exc() ：

import traceback

def reader(args):

try:

# Insert stuff to be multiprocessed here

return args[0]['that']

except:

print "FATAL: reader({0}) exited while multiprocessing".format(args)

traceback.print_exc()

現(xiàn)在，當(dāng)您發(fā)現(xiàn)崩潰時(shí)，您會(huì)看到以下內(nèi)容：

FATAL: reader([{'crash', 'this'}]) exited while multiprocessing

Traceback (most recent call last):

File "foo.py", line 19, in __init__

self.run(task_q, result_q)

File "foo.py", line 46, in run

raise ValueError

ValueError

源代碼：

"""

multi_pipe.py

"""

from multiprocessing import Process, Pipe

import time

def reader_proc(pipe):

## Read from the pipe; this will be spawned as a separate Process

p_output, p_input = pipe

p_input.close() # We are only reading

while True:

msg = p_output.recv() # Read from the output pipe and do nothing

if msg=='DONE':

break

def writer(count, p_input):

for ii in xrange(0, count):

p_input.send(ii) # Write 'count' numbers into the input pipe

p_input.send('DONE')

if __name__=='__main__':

for count in [10**4, 10**5, 10**6]:

# Pipes are unidirectional with two endpoints: p_input ------> p_output

p_output, p_input = Pipe() # writer() writes to p_input from _this_ process

reader_p = Process(target=reader_proc, args=((p_output, p_input),))

reader_p.daemon = True

reader_p.start() # Launch the reader process

p_output.close() # We no longer need this part of the Pipe()

_start = time.time()

writer(count, p_input) # Send a lot of stuff to reader_proc()

p_input.close()

reader_p.join()

print("Sending {0} numbers to Pipe() took {1} seconds".format(count,

(time.time() - _start)))

"""

multi_queue.py

"""

from multiprocessing import Process, Queue

import time

import sys

def reader_proc(queue):

## Read from the queue; this will be spawned as a separate Process

while True:

msg = queue.get() # Read from the queue and do nothing

if (msg == 'DONE'):

break

def writer(count, queue):

## Write to the queue

for ii in range(0, count):

queue.put(ii) # Write 'count' numbers into the queue

queue.put('DONE')

if __name__=='__main__':

pqueue = Queue() # writer() writes to pqueue from _this_ process

for count in [10**4, 10**5, 10**6]:

### reader_proc() reads from pqueue as a separate process

reader_p = Process(target=reader_proc, args=((pqueue),))

reader_p.daemon = True

reader_p.start() # Launch reader_proc() as a separate python process

_start = time.time()

writer(count, pqueue) # Send a lot of stuff to reader()

reader_p.join() # Wait for the reader to finish

print("Sending {0} numbers to Queue() took {1} seconds".format(count,

(time.time() - _start)))

"""

multi_joinablequeue.py

"""

from multiprocessing import Process, JoinableQueue

import time

def reader_proc(queue):

## Read from the queue; this will be spawned as a separate Process

while True:

msg = queue.get() # Read from the queue and do nothing

queue.task_done()

def writer(count, queue):

for ii in xrange(0, count):

queue.put(ii) # Write 'count' numbers into the queue

if __name__=='__main__':

for count in [10**4, 10**5, 10**6]:

jqueue = JoinableQueue() # writer() writes to jqueue from _this_ process

# reader_proc() reads from jqueue as a different process...

reader_p = Process(target=reader_proc, args=((jqueue),))

reader_p.daemon = True

reader_p.start() # Launch the reader process

_start = time.time()

writer(count, jqueue) # Send a lot of stuff to reader_proc() (in different process)

jqueue.join() # Wait for the reader to finish

print("Sending {0} numbers to JoinableQueue() took {1} seconds".format(count,

(time.time() - _start)))

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