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I'm curious in how the Global Interpreter Lock in python actually works. If I have a c++ application launch four separate instances of a python script will they run in parallel on separate cores, or does the GIL go even deeper then just the single process that was launched and control all python process's regardless of the process that spawned it?
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When calling a linux binary which takes a relatively long time through Python's subprocess module, does this release the GIL? Yes, it releases the Global Interpreter Lock (GIL) in the calling process.
The GIL allows only one OS thread to execute Python bytecode at any given time, and the consequence of this is that it's not possible to speed up CPU-intensive Python code by distributing the work among multiple threads. This is, however, not the only negative effect of the GIL.
Alternative Python interpreters: Python has multiple interpreter implementations. CPython, Jython, IronPython and PyPy, written in C, Java, C# and Python respectively, are the most popular ones. GIL exists only in the original Python implementation that is CPython.
The GIL only affects threads within a single process. The multiprocessing module is in fact an alternative to threading that lets Python programs use multiple cores &c. Your scenario will easily allow use of multiple cores, too.
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As Alex Martelli points out you can indeed avoid the GIL by running multiple processes, I just want to add and point out that the GIL is a limitation of the implementation (CPython) and not of Python in general, it's possible to implement Python without this limitation. Stackless Python comes to mind.
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