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    <p><strong>os.fork</strong></p> <p>A fork will clone the parent process, which in this case, is your Django stack. Since you're merely wanting to run a separate python script, this seems like an unnecessary amount of bloat.</p> <p><strong>subprocess</strong></p> <p>Using <code>subprocess</code> is expected to be interactive. In other words, while you can use this to effectively spawn off a process, it's expected that at some point you'll terminate it when finished. It's possible Python might clean up for you if you leave one running, but my guess would be that this will actually result in a memory leak.</p> <p><strong>threads</strong></p> <p>Threads are defined units of logic. They start when their <code>run()</code> method is called, and terminate when the <code>run()</code> method's execution ends. This makes them well suited to creating a branch of logic that will run outside the current scope. However, as you mentioned, they are subject to the Global Interpreter Lock.</p> <p><strong>multiprocessing</strong></p> <p>This is basically threads on steroids. It has the benefits of a thread, but is not subject to the Global Interpreter Lock, and can take advantage of multi-core architectures. However, they are more complicated to work with as a result.</p> <p>So, your choices really come down to threads or multiprocessing. If you can get by with a thread and it makes sense for your application, go with a thread. Otherwise, use multiprocessing.</p>
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    1. COThanks Chris. Could you elaborate a little bit more on **Threads** -> 'subject to GDI' and **Processes** -> 'more complicated to work with as a result'. _THREADS_: If, say, 2 different web requests spawn 2 different threads that work on different resources, will they be able to run concurrently? My guess is.. not (especially if coming from a single-process mod_wsgi). But it sounds like, according to Graham, they will not block serving other requests, which is still the most important thing. _PROCESSES_: is the difficulty related to making them communicate, or is there something else? Thanks!
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    2. COThe Global Interpreter Lock is only an issue with CPython implementations. That particular version of the Python interpreter enforces a hard limit of one thread at a time being able to work with bytecode. It's probably nothing you'll need to worry about, but in terms of interoperability, it's something to be aware of.
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    3. COThreads are almost stupidly simple to work with. You subclass `Thread` define `__init__` and `run` and you're off to the races. Multiprocessing deals with the concept of pools of workers. There's a lot more intialization and you have to carefully manage what's going on. It's the same reason that many modern-day applications *still* don't actually utilize multiple cores. You can do amazing stuff with all that processing power, but it's like orchestrating a symphony -- you'll have to put in some work to get it just right.
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