Python News Today Release 3.13 November 2025 [updated] -

— The RealPython Team, November 2025

When an uncaught exception occurs in the REPL or a Jupyter notebook, you can now type explain to get an AI-generated (local, privacy-safe) explanation of the error, possible causes, and a fix snippet.

If you want to experiment:

The JIT works by compiling simple Python bytecode sequences into native machine code at runtime, specializing for common operations (e.g., integer addition, attribute lookups, calls to built-in functions).

| Removed Feature | Deprecated since | Replacement | |----------------|----------------|-------------| | cgi module | Python 3.11 | email or multipart (or FastAPI/Flask) | | telnetlib | Python 3.11 | paramiko or subprocess + SSH | | asyncio.coroutine (yield from) | Python 3.10 | async / await | | typing.io / typing.re | Python 3.8 | collections.abc or re directly | | distutils (fully gone) | Python 3.10 | setuptools or pyproject.toml | python news today release 3.13 november 2025

The Steering Council chose sub-interpreters over a GIL-less build (still available as --disable-gil for the brave) because sub-interpreters maintain full C-extension compatibility – a critical requirement for the scientific and data science ecosystems (NumPy, Pandas, TensorFlow all work unchanged). Takeaway: For CPU-bound workloads, rewrite your multiprocessing code to use interpreters.Pool . For I/O-bound tasks, asyncio remains king. 2. JIT Compilation Graduates from Experimental (PEP 744) PEP 744 , the Copy-and-Patch JIT compiler introduced as an experiment in Python 3.13 beta, is now enabled by default on x86-64 and ARM64 builds.

This feature uses a small on-device LLM (Mistral-7B distilled) that ships with Python 3.13 – optional, install via python -m ensure_explain . In response to global supply chain security mandates (including upcoming US Executive Order 14110 compliance), Python 3.13 now includes a native Software Bill of Materials (SBOM) generator. — The RealPython Team, November 2025 When an

For the first time, Python can run truly parallel CPU-bound code without the Global Interpreter Lock (GIL) being a bottleneck – but not via removing the GIL entirely. Instead, 3.13 introduces a robust interpreters module that allows you to spawn isolated sub-interpreters, each with its own GIL, sharing only specific immutable objects.