python - 如何在 Python 中使用线程？

Question

我想要一个清晰的示例，显示任务被划分到多个线程中。

Answer 1

自从 2010 年提出这个问题以来，如何使用 Python 使用 map 进行简单的多线程处理已经有了真正的简化。 和 pool 。

下面的代码来自您绝对应该查看的文章/博客文章(无隶属关系)- Parallelism in one line: A Better Model for Day to Day Threading Tasks 。我将在下面进行总结 - 它最终只是几行代码:

from multiprocessing.dummy import Pool as ThreadPool
pool = ThreadPool(4)
results = pool.map(my_function, my_array)

哪个是多线程版本:

results = []
for item in my_array:
    results.append(my_function(item))

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描述

Map is a cool little function, and the key to easily injecting parallelism into your Python code. For those unfamiliar, map is something lifted from functional languages like Lisp. It is a function which maps another function over a sequence.

Map handles the iteration over the sequence for us, applies the function, and stores all of the results in a handy list at the end.

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实现

Parallel versions of the map function are provided by two libraries:multiprocessing, and also its little known, but equally fantastic step child:multiprocessing.dummy.

multiprocessing.dummy 与多处理模块完全相同，but uses threads instead ( an important distinction - 对 CPU 密集型任务使用多个进程；对 I/O(以及期间)使用线程):

multiprocessing.dummy replicates the API of multiprocessing, but is no more than a wrapper around the threading module.

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/',
]

# 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()

以及计时结果:

Single thread:   14.4 seconds
       4 Pool:   3.1 seconds
       8 Pool:   1.4 seconds
      13 Pool:   1.3 seconds

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传递多个参数(工作方式如下 only in Python 3.3 and later ):

传递多个数组:

results = pool.starmap(function, zip(list_a, list_b))

或者传递一个常量和一个数组:

results = pool.starmap(function, zip(itertools.repeat(constant), list_a))

如果您使用的是早期版本的 Python，则可以通过 this workaround 传递多个参数)。

(感谢 user136036 的有用评论。)