8 Years Ago I Learned Python 3.8. Now We’re at 3.15
Last Updated on August 25, 2026 by Editorial Team
Author(s): Hamza Boulahia
Originally published on Towards AI.
Here’s what you should know about Python’s evolution.
I started learning Python right after finishing my Master’s in Applied Mathematics. My initial goal was to use it for data science and eventually land a Data Scientist job. I had previously used R, but I wanted something more versatile and that’s useful for more than just Data Science. What started simply as a practical skill to complement my mathematical background eventually grew into a much deeper interest in programming, especially as the fields of ML/DL and AI began evolving so rapidly.
After the introduction, the article walks through Python’s evolution from 3.8 toward 3.15, grouping major changes into four themes: more expressive and convenient syntax (walrus operator, positional-only parameters, pattern matching, and additional string/data utilities), stronger and more “native” type hints (structural typing with Protocol/TypedDict, built-in generic syntax, union syntax, improved decorator typing, and lazy evaluation of annotations via recent PEPs), major runtime and speed improvements in CPython (including Faster CPython work, adaptive specialization, reduced overhead, parallelism changes and GIL developments, plus experimental-to-improving JIT compilation), and better tooling and developer comfort (clearer errors, richer debugging features, structured concurrency and exception grouping, standard-library expansions, removal of legacy modules, and system-level improvements like UTF-8 as default encoding and better profiling integration).
Read the full blog for free on Medium.
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