http://code.activestate.com/recipes/tags/parallel/2011-06-12T16:34:12-07:00ActiveState Code Recipes2011-06-12T16:34:12-07:00Barry Walkerhttp://code.activestate.com/recipes/users/4177147/http://code.activestate.com/recipes/577750-for-amiga-heads-only-par-as-a-volume-in-read-mode-/

<p style="color: grey"> Python recipe 577750 by <a href="/recipes/users/4177147/">Barry Walker</a> (<a href="/recipes/tags/amiga/">amiga</a>, <a href="/recipes/tags/demo/">demo</a>, <a href="/recipes/tags/parallel/">parallel</a>, <a href="/recipes/tags/parallel_port/">parallel_port</a>, <a href="/recipes/tags/port/">port</a>, <a href="/recipes/tags/read/">read</a>). </p> <p>PAR: as a VOLUME in READ mode using Python 1.4 onwards on Classic AMIGAs...</p> <p>Many years ago Irmen de Jong ported Python to the Classic AMIGA range of computers, (many thanks Irmen for your time in doing so). The versions were at least 1.4.x to 2.0.1 and now someone else has included version 2.4.6.</p> <p>This gives we lowly users of the AMIGA at least a chance to see and use Python in some guise or another. This code shows how to access the AMIGA parallel port for 8 bit READ only. This is so that ADCs could be attached to the port, read by Python code EASILY and utilised as a Data Logger/Transient Recorder, as just one example.</p> <p>There needs to be a single HW WIRE link only from the 23 way video port to the 25 way parallel port for this to work. See the archive......</p> <p><a href="http://aminet.net/package/docs/hard/PAR_READ" rel="nofollow">http://aminet.net/package/docs/hard/PAR_READ</a></p> <p>......on how to set about this extremely simple task.</p> <p>NO knowledge of the parallel port programming is needed at all to grab 8 bit data from it using Python and other languages; (ARexx is used in the archive above).</p> <p>There is a flaw, NOTE:- NOT A BUG!, in the Python code but for this DEMO it is ignored. ;o)</p> <p>I'll let all you big guns work out what it is; you will need a good working knowledge of the Classic AMIGA.</p> <p>Enjoy finding simple solutions to often very difficult problems. ;o)</p> <p>This code is Public Domain and you may do with it as you please.</p> <p>Bazza...</p>

2010-04-02T00:14:38-07:00Kevin L. Sitzehttp://code.activestate.com/recipes/users/4173535/http://code.activestate.com/recipes/577171-parallelize-your-shell-commands/

<p style="color: grey"> Bash recipe 577171 by <a href="/recipes/users/4173535/">Kevin L. Sitze</a> (<a href="/recipes/tags/fifo/">fifo</a>, <a href="/recipes/tags/multiprocessing/">multiprocessing</a>, <a href="/recipes/tags/parallel/">parallel</a>). Revision 2. </p> <p>This script is used to processes a batch job of commands in parallel. The script dispatches new commands up to a user specified limit, each generated from a template provided on the command line using arguments taken from STDIN. The basic combining semantics are similar to "xargs -1", though support for multiple arguments and parallel processing of commands are provided.</p>

2009-04-02T19:41:10-07:00Miki Tebekahttp://code.activestate.com/recipes/users/4086267/http://code.activestate.com/recipes/576709-parallel-map/

<p style="color: grey"> Python recipe 576709 by <a href="/recipes/users/4086267/">Miki Tebeka</a> (<a href="/recipes/tags/algorithm/">algorithm</a>, <a href="/recipes/tags/map/">map</a>, <a href="/recipes/tags/parallel/">parallel</a>). Revision 3. </p> <p>Implementation of parallel map (processes).</p> <p>This is a Unix only version.</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>