Python 3.12 Brings New Features and Fixes - Slashdot

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"The Python programming language releases new versions yearly, with a feature-locked beta release in the first half of the year and the final release toward the end of the year," writes InfoWorld.

So now Python 3.12 beta 1 has just been released, and InfoWorld compiled a list of its most significant new features. Some highlights:

- The widely used Linux profiler tool perf works with Python, but only returns information about what's happening at the C level in the Python runtime. Information about actual Python program functions doesn't show up. Python 3.12 enables an opt-in mode to allow perf to harvest details about Python programs...

- Programs can run as much as an order of magnitude slower when run through a debugger or profiler. PEP 669 provides hooks for code object events that profilers and debuggers can attach to, such as the start or end of a function. A callback function could be registered by a tool to fire whenever such an event is triggered. There will still be a performance hit for profiling or debugging, but it'll be greatly reduced...

- Comprehensions, a syntax that lets you quickly construct lists, dictionaries, and sets, are now constructed "inline" rather than by way of temporary objects. The speedup for this has been clocked at around 11% for a real-world case and up to twice as fast for a micro-benchmark.

- Python's type-hinting syntax, added in Python 3.5, allows linting tools to catch a wide variety of errors ahead of time. With each new version, typing in Python gains features to cover a broader and more granular range of use cases... The type parameter syntax provides a cleaner way to specify types in a generic class, function, or type alias...

- Every object in Python has a reference count that tracks how many times other objects refer to it, including built-in objects like None. PEP 683 allows objects to be treated as "immortal," so that they never have their reference count changed. Making objects immortal has other powerful implications for Python in the long run. It makes it easier to implement multicore scaling, and to implement other optimizations (like avoiding copy-on-write) that would have been hard to implement before.

- With earlier versions of Python, the base size of an object was 208 bytes. Objects have been refactored multiple times over the last few versions of Python to make them smaller, which doesn't just allow more objects to live in memory but helps with cache locality. As of Python 3.12, the base size of an object is now 96 bytes — less than half of what it used to be.