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Python 3.12 was released today, with improvements to speed and efficiency, reports InfoWorld. Core developers explained the improvements at this year’s PyCon convention in Salt Lake City, Utah, including efforts to reduce Python’s memory use, make the interpreter faster, and optimize compilation for more efficient code:
Subinterpreters is a mechanism where the Python runtime can have multiple interpreters running together inside a single process, as opposed to each interpreter being isolated in its own process (the current multiprocessing mechanism)… While subinterpreters have been available in the Python runtime for some time now, they haven’t had an interface for the end user. Also, the messy state of Python’s internals hasn’t allowed subinterperters to be used effectively. With Python 3.12, core python developer Eric Snow and his cohort cleaned up Python’s internals enough to make subinterpreters useful, and they are adding a minimal module to the Python standard library called interpreters. This gives programmers a rudimentary way to launch subinterpreters and execute code on them.
Snow’s own initial experiments with subinterpreters significantly outperformed threading and multiprocessing. One example, a simple web service that performed some CPU-bound work, maxed out at 100 requests per second with threads, and 600 with multiprocessing. But with subinterpreters, it yielded 11,500 requests, and with little to no drop-off when scaled up from one client. The interpreters module has very limited functionality right now, and it lacks robust mechanisms for sharing state between subinterpreters. But Snow believes by Python 3.13 a good deal more functionality will appear, and in the interim developers are encouraged to experiment…
Python 3.11 introduced new bytecodes to the interpreter, called adaptive instructions. These instructions can be replaced automatically at runtime with versions specialized for a given Python type, a process called quickening. This saves the interpreter the step of having to look up what types the objects are, speeding up the whole process enormously. For instance, if a given addition operation regularly takes in two integers, that instruction can be replaced with one that assumes the operands are both integers… Python 3.12 has more adaptive specialization opcodes…
And starting with Python 3.12, object headers now use 96 bytes, which InfoWorld reports is “slightly less than half of what it was before.”
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