Unlocking Python’s speed: how recent updates are making Python faster

Python, a language loved for its simplicity, has undergone significant performance improvements since version 3.11. It’s impressive to witness how these optimizations are transforming the speed of a 30-year-old language. From specialized, adaptive interpreters to more efficient memory management and the introduction of JIT compilation, Python’s recent versions are evolving rapidly, offering performance gains of ~10%-60% across various workloads.

These changes are making Python not only faster for core functionality but also beneficial for libraries like NumPy and Pandas, making it even more relevant for data-centric applications.

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