用map函数来完成Python并行任务的简单示例

#Example.py
'''
Standard Producer/Consumer Threading Pattern
'''
 
import time
import threading
import Queue
 
class Consumer(threading.Thread):
  def __init__(self, queue):
    threading.Thread.__init__(self)
    self._queue = queue
 
  def run(self):
    while True:
      # queue.get() blocks the current thread until
      # an item is retrieved.
      msg = self._queue.get()
      # Checks if the current message is
      # the "Poison Pill"
      if isinstance(msg, str) and msg == 'quit':
        # if so, exists the loop
        break
      # "Processes" (or in our case, prints) the queue item 
      print "I'm a thread, and I received %s!!" % msg
    # Always be friendly!
    print 'Bye byes!'
 
def Producer():
  # Queue is used to share items between
  # the threads.
  queue = Queue.Queue()
 
  # Create an instance of the worker
  worker = Consumer(queue)
  # start calls the internal run() method to
  # kick off the thread
  worker.start()
 
  # variable to keep track of when we started
  start_time = time.time()
  # While under 5 seconds..
  while time.time() - start_time < 5:
    # "Produce" a piece of work and stick it in
    # the queue for the Consumer to process
    queue.put('something at %s' % time.time())
    # Sleep a bit just to avoid an absurd number of messages
    time.sleep(1)
 
  # This the "poison pill" method of killing a thread.
  queue.put('quit')
  # wait for the thread to close down
  worker.join()
 
if __name__ == '__main__':
  Producer()

#Example2.py
'''
A more realistic thread pool example
'''
 
import time
import threading
import Queue
import urllib2
 
class Consumer(threading.Thread):
  def __init__(self, queue):
    threading.Thread.__init__(self)
    self._queue = queue
 
  def run(self):
    while True:
      content = self._queue.get()
      if isinstance(content, str) and content == 'quit':
        break
      response = urllib2.urlopen(content)
    print 'Bye byes!'
 
def Producer():
  urls = [
    'http://www.python.org', 'http://www.yahoo.com'
    'http://www.scala.org', 'http://www.google.com'
    # etc..
  ]
  queue = Queue.Queue()
  worker_threads = build_worker_pool(queue, 4)
  start_time = time.time()
 
  # Add the urls to process
  for url in urls:
    queue.put(url) 
  # Add the poison pillv
  for worker in worker_threads:
    queue.put('quit')
  for worker in worker_threads:
    worker.join()
 
  print 'Done! Time taken: {}'.format(time.time() - start_time)
 
def build_worker_pool(queue, size):
  workers = []
  for _ in range(size):
    worker = Consumer(queue)
    worker.start()
    workers.append(worker)
  return workers
 
if __name__ == '__main__':
  Producer()

urls = ['http://www.yahoo.com', 'http://www.reddit.com']
results = map(urllib2.urlopen, urls)

results = []
for url in urls:
  results.append(urllib2.urlopen(url))

from multiprocessing import Pool
from multiprocessing.dummy import Pool as ThreadPool

pool = ThreadPool()

pool = ThreadPool(4) # Sets the pool size to 4

import urllib2
from multiprocessing.dummy import Pool as ThreadPool
 
urls = [
  'http://www.python.org',
  'http://www.python.org/about/',
  'http://www.onlamp.com/pub/a/python/2003/04/17/metaclasses.html',
  'http://www.python.org/doc/',
  'http://www.python.org/download/',
  'http://www.python.org/getit/',
  'http://www.python.org/community/',
  'https://wiki.python.org/moin/',
  'http://planet.python.org/',
  'https://wiki.python.org/moin/LocalUserGroups',
  'http://www.python.org/psf/',
  'http://docs.python.org/devguide/',
  'http://www.python.org/community/awards/'
  # etc..
  ]
 
# Make the Pool of workers
pool = ThreadPool(4)
# Open the urls in their own threads
# and return the results
results = pool.map(urllib2.urlopen, urls)
#close the pool and wait for the work to finish
pool.close()
pool.join()

# results = []
# for url in urls:
#  result = urllib2.urlopen(url)
#  results.append(result)
 
# # ------- VERSUS ------- #
 
# # ------- 4 Pool ------- #
# pool = ThreadPool(4)
# results = pool.map(urllib2.urlopen, urls)
 
# # ------- 8 Pool ------- #
 
# pool = ThreadPool(8)
# results = pool.map(urllib2.urlopen, urls)
 
# # ------- 13 Pool ------- #
 
# pool = ThreadPool(13)
# results = pool.map(urllib2.urlopen, urls)

#            Single thread: 14.4 Seconds
#               4 Pool:  3.1 Seconds
#               8 Pool:  1.4 Seconds
#               13 Pool:  1.3 Seconds

import os
import PIL
 
from multiprocessing import Pool
from PIL import Image
 
SIZE = (75,75)
SAVE_DIRECTORY = 'thumbs'
 
def get_image_paths(folder):
  return (os.path.join(folder, f)
      for f in os.listdir(folder)
      if 'jpeg' in f)
 
def create_thumbnail(filename):
  im = Image.open(filename)
  im.thumbnail(SIZE, Image.ANTIALIAS)
  base, fname = os.path.split(filename)
  save_path = os.path.join(base, SAVE_DIRECTORY, fname)
  im.save(save_path)
 
if __name__ == '__main__':
  folder = os.path.abspath(
    '11_18_2013_R000_IQM_Big_Sur_Mon__e10d1958e7b766c3e840')
  os.mkdir(os.path.join(folder, SAVE_DIRECTORY))
 
  images = get_image_paths(folder)
 
  for image in images:
       create_thumbnail(Image)

import os
import PIL
 
from multiprocessing import Pool
from PIL import Image
 
SIZE = (75,75)
SAVE_DIRECTORY = 'thumbs'
 
def get_image_paths(folder):
  return (os.path.join(folder, f)
      for f in os.listdir(folder)
      if 'jpeg' in f)
 
def create_thumbnail(filename):
  im = Image.open(filename)
  im.thumbnail(SIZE, Image.ANTIALIAS)
  base, fname = os.path.split(filename)
  save_path = os.path.join(base, SAVE_DIRECTORY, fname)
  im.save(save_path)
 
if __name__ == '__main__':
  folder = os.path.abspath(
    '11_18_2013_R000_IQM_Big_Sur_Mon__e10d1958e7b766c3e840')
  os.mkdir(os.path.join(folder, SAVE_DIRECTORY))
 
  images = get_image_paths(folder)
 
  pool = Pool()
    pool.map(create_thumbnail,images)
    pool.close()
    pool.join()