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In June, the Python steering council announced that it was pausing work on the JIT in CPython's main branch until there was an accepted Python Enhancement Proposal (PEP) that addressed concerns about maintenance, compatibility, and set clear success metrics as well as a timeline for completion. After [....] months of discussion, the JIT maintainers have withdrawn the PEP. For now, it appears that development on the once-promising project has come to an end

Heads-up for anyone with Lambda functions still on python3.10. AWS deprecates the runtime on Oct 31, 2026. Functions keep running, but they stop getting patches, the console won't let you edit them, and in 2027 AWS blocks creating new ones (Jul 29) and then updating existing ones (Aug 31).

The Python side is the real work. A few things that bit people:

- distutils is gone in 3.12. Anything still importing it (old setup.py tooling, some older libraries) breaks. setuptools or packaging usually covers it.

- cgi, crypt and telnetlib are removed in 3.13 (PEP 594 "dead batteries").

- python3.12+ on Lambda runs on Amazon Linux 2023 instead of AL2, so compiled wheels and layers (numpy, psycopg2, cryptography and similar) need rebuilding.

- python3.11 is a short stop. It's still on AL2 and is deprecated Jun 30, 2027.

Quick way to find affected functions (per Region):

aws lambda list-functions --function-version ALL --query "Functions[?Runtime=='python3.10'].[FunctionName,Version]" --output text

Disclosure: I made a free AWS end-of-support tracker, and the full write-up with AWS source links is here: https://eolwatch.pages.dev/guides/lambda-python-3-10-deprecation

What else broke for you going 3.10 → 3.12/3.13?

The results are out for the 2026 Python Typing Survey (1,794 responses).

The full writeup can be read at: https://engineering.fb.com/2026/10/27/developer-tools/python-typing-survey-2026-ai-tools-checker-landscape/

TLDR: - Newer type checkers gained market share, and speed was the most common reason for choosing a checker (56.5%). - The share of respondents who said types make AI-generated code more reliable rose from 18.5% in 2025 to 38.4% in 2026. - AI tools wrote type hints for 42.5% of respondents, and 24.4% said an AI coding tool ran their type checker. - Missing type information in third-party libraries remained the most common difficulty, reported by 65.1% of respondents. - Better Callable syntax was the most requested missing feature, at 45.7%.

Has anyone else wanted more out of dataclass? Like transactions, undo/redo, lambda initializers that take parameters (as other field values) and call them in the correct order and no post_init (does not survive a diamond inheritance)? Transactional field values started me down this trek for a "ReactJS" like project to manage the view graph.

It's difficult to tell whether a name is available in PyPI, where searching for package name doesn't guarantee that it's available. Imagine how stressful it is to build a project, setting up its website, repository, and so on, only to find when you’re ready to publish that the package name is unavailable.

Reserver, a small automation tool that helps Python developers claim a name early through PyPI, was removed by PyPI stating "[it] promotes name squatting." But removing Reserver doesn’t prevent people from claiming names through the existing publishing process nor make name availability clearer. We believe removing the tool instead of addressing the underlying issue is a vivid example of poor community management.

Read more: “Reserver is gone, but PyPI’s name reservation problem isn’t!”

⁉️ Why does pydantic>=2.11 sit in your pyproject.toml? Is it the lowest version that actually works, or just a tool default? And what evidence backs that claim?

💡 Dependency declarations are claims about package versions, yet they often follow tool defaults and habit rather than deliberate choice. Choosing them by the environment they constrain and pairing each with supporting evidence narrows the gap between what a project claims and what it actually verifies.

📰 Curious about the deep dive with worked examples for libraries, applications, and development dependencies? Check out Towards closing the gap between declaring and verifying Python dependencies.

💬 Comments and feedback are most welcome.