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    <p>There seems to be a misunderstanding in your question.</p> <p>A cron job is a scheduled task that runs at a given interval of time. A program running continuously doesn't need to be scheduled, aside from being launched at boot.</p> <p>First, multi-threading in Python suffers the <a href="http://wiki.python.org/moin/GlobalInterpreterLock" rel="nofollow">GIL</a>, so unless you are calling multi-threading aware library functions or your computations are I/O bound (often blocked by input/output such as disk access, network access and such) that releases the GIL, you will only have an insubstantial gain by using threading. You should though consider using the <a href="http://docs.python.org/library/multiprocessing.html" rel="nofollow">multiprocessing</a> package for parallel computing. Other options are NumPy-based calculations when the library is compiled with OpenMP or using a task-based parallel framework such as <a href="https://code.google.com/p/scoop/" rel="nofollow">SCOOP</a> or <a href="http://celeryproject.org/" rel="nofollow">Celery</a>.</p> <p>As stated in the comments, memory management is built in in Python and you won't have to worry about it apart from deleting unused instances or elements. Python will garbage collect your program automatically for every element that doesn't have any variable bound to it, so be sure to delete them or let them fall off-scope accordingly.</p> <p>On a side-note, be careful with objects destructors in Python, they tend to exhibit a different behavior than other Object Oriented languages. I recommend you reading of this matter before using them.</p>
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    1. PORunning a continuous Python process and memory management
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    1. USMatti Lyra
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    1. COThere are also a handful of great persistent process frameworks for writing daemons of all sorts. Off the top of my head: Twisted, Eventlet, Gevent.
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      1. USJonathan Vanasco
 

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