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<!doctype html>
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<meta charset="utf-8" />
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<title>
使用 Python 装饰器来将普通函数加入任务队列 - 雪地
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<h1>使用 Python 装饰器来将普通函数加入任务队列</h1>
<div class="read-more clearfix">
<span class="date">2016/7/14 23:41 下午</span>
<span>posted in </span>
<span class="posted-in"><a href='Python.html'>Python</a></span>
<span class="comments">
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<p>对于操作『函数对象』来说，使用 Python 装饰器是一种非常优雅，非常 Pythonic 的一个方式。而在这篇文章中，对于任何一个普通的函数，只需要在函数定义前加一个装饰器调用，即可使得这一函数被调用时自动加入特定的任务队列，成为异步调用，而不会阻塞主线程。</p>
<span id="more"></span><!-- more -->
<h2 id="toc_0">实现 Producer/Consumer 型任务队列</h2>
<pre><code class="language-python"># -*- coding: utf-8 -*-
from Queue import Queue
from threading import Thread
from collections import namedtuple
Job = namedtuple('Job', ('func', 'args', 'kwargs', 'result_obj'))
</code></pre>
<p>首先，我们先声明了一个 namedtuple ，其中包含以下几个元素：</p>
<ol>
<li><code>func</code> ：需要加入任务队列的目标函数对象</li>
<li><code>args</code> 和 <code>kwargs</code> ：目标函数对象的参数</li>
<li><code>result_obj</code> ：用于保存目标函数返回值的一个字典， 装饰器函数将目标函数加入任务队列之后，会直接返回一个<code>{'result': None, 'done': False}</code>的字典。等到目标函数异步执行完成之后， Worker 会用返回值替换这一字典的<code>result</code>，并设置<code>done</code>为<code>True</code></li>
</ol>
<pre><code class="language-python">class Worker(Thread):
def __init__(self, queue):
"""
:type queue: Queue
"""
super(Worker, self).__init__()
self.queue = queue
self._stopped = False
self._stop_done = False
def run(self):
while True:
if self._stopped is True:
break
task = self.queue.get()
result = task.func(*task.args, **task.kwargs)
task.result_obj['result'] = result
task.result_obj['done'] = True
self._stop_done = True
def stop(self):
self._stopped = True
</code></pre>
<p>Worker 和普通的 Consumer 定义基本没有区别，唯一要注意的地方是，记得要用函数返回值，替换掉任务返回值字典的<code>'result'</code>，并修改任务状态，即</p>
<pre><code class="language-python">task.result_obj['result'] = result
task.result_obj['done'] = True
</code></pre>
<pre><code class="language-python">
class QueueHandler(object):
def __init__(self, workers=5):
self.job_queue = Queue()
self.workers = [Worker(self.job_queue) for i in xrange(workers)]
for worker in self.workers:
worker.setDaemon(True)
worker.start()
def queue_up(self, func):
def _queue_up(*args, **kwargs):
tmp_obj = {'result': None, 'done': False}
self. job_queue.put(
Job(
func = func,
args = args,
kwargs = kwargs,
result_obj=tmp_obj
)
)
return tmp_obj
return _queue_up
</code></pre>
<p>同样是比较标准的 Producer ，其中<code>queue_up</code>函数就是这次的主角了。对于目标函数，先构建一个返回值字典，然后将目标函数和参数加入任务队列，最后返回这一返回值字典。非常简单的结构，但是使用起来非常的方便。</p>
<h2 id="toc_1">实际测试</h2>
<p>这里我构造了一个用来测试的代码</p>
<pre><code class="language-python">import time, random
testQueue = QueueHandler()
class TestClass(object):
def __init__(self):
self.some_value = 10
self.some_str = "Empty"
@testQueue.queue_up
def some_operation(self, jobid, some_para, another_para='blablabla'):
time.sleep(random.randrange(1,5))
self.some_value = some_para
self.some_str = another_para
print "ID: {} ---Now, value: {}, str: {}\n".format(jobid, self.some_value, self.some_str)
return jobid+100000
if __name__ == '__main__':
testClass = TestClass()
rs = []
for i in range(10):
rs.append(
testClass.some_operation(i, i+1000, another_para='{0}'.format('-'*i))
)
for i in range(10):
time.sleep(1)
print rs
</code></pre>
<p>读者可以尝试删除掉<code>some_operation</code>函数前面的装饰器，对比有无这个装饰器对程序运行的影响。</p>
<p>可以看到，对于需要测试的<code>some_operation</code>函数，我仅仅是在其定义前加上了一个装饰器的调用，就使得这个函数的执行不会阻塞主线程了。并且对于异步调用函数的返回值，也很好的进行了保留传递。</p>
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