http://code.activestate.com/recipes/tags/pool-thread/2008-11-30T05:42:59-08:00ActiveState Code Recipes2008-11-30T05:42:59-08:00Louis RIVIEREhttp://code.activestate.com/recipes/users/4035877/http://code.activestate.com/recipes/576576-thread-pool/

<p style="color: grey"> Python recipe 576576 by <a href="/recipes/users/4035877/">Louis RIVIERE</a> (<a href="/recipes/tags/design_pattern/">design_pattern</a>, <a href="/recipes/tags/pool/">pool</a>, <a href="/recipes/tags/threads/">threads</a>, <a href="/recipes/tags/thread_pool/">thread_pool</a>). Revision 4. </p> <p>Easy to use Thread Pool with a dynamically adjustable pool size.</p>

2008-09-17T17:01:21-07:00david decotignyhttp://code.activestate.com/recipes/users/4129454/http://code.activestate.com/recipes/576462-processingpool-variation-which-allows-multiple-thr/

<p style="color: grey"> Python recipe 576462 by <a href="/recipes/users/4129454/">david decotigny</a> (<a href="/recipes/tags/map/">map</a>, <a href="/recipes/tags/parallel/">parallel</a>, <a href="/recipes/tags/pool/">pool</a>, <a href="/recipes/tags/processing/">processing</a>, <a href="/recipes/tags/threads/">threads</a>). Revision 3. </p> <p>processing.Pool (<a href="http://pypi.python.org/pypi/processing" rel="nofollow">http://pypi.python.org/pypi/processing</a>) is a nice tool to "parallelize" map() on multiple CPUs. However, imagine you have X threads which send the same request Pool.map(getNthPrimeNumber, [100000, 10000000, 10000]) at (almost) the same time. Obviously, you don't want to compute X times getNthPrimeNumber for 100000, 10000000, 10000... unless you have 3.X processors available. You would like one thread to submit the 3 requests, and then the X-1 others would notice that the requests have already been submitted and will then just wait for the result. This is what this code is about: a kind of "trensient memoize" for processing.Pool::imap().</p>