What key improvements in Python 3.12 (and upcoming 3.13 features) make the language more performant for backend services and ML workloads in 2025?

Details how recent enhancements like better f-string parsing, sub-interpreters, and memory optimization affect Python’s backend and ML viability.

PEP 701 delivers flexible f-string parsing, allowing multiline expressions and comments within f strings, improving developer ergonomics. PEP 684 / 554 introduces isolated subinterpreters each with its own GIL, enabling true parallelism in Python 3.12 and above when leveraged with libraries like multiprocessing.shared_memory. This reduces Python's concurrency limitations in backend and data processing contexts. Performance gains: CPython 3.12 includes BOLT optimizer and new profiling/debug APIs per PEP 669, yielding ~5% runtime improvement over 3.11, which accumulates significantly in large-scale workloads (e.g. ETL or ML model serving).