Python

Python 3.15 beta 1 is out! This is a really impactful release, with some really big additions. A new lazy import system, a powerful sampling profiler, not one but two new builtins, the usual color/types/errors updates, and lots of key changes for developers.

AI suddenly passed the “more time saved than spent” point around December 2025. A little late, I’ve finally started using agentic AI in various places over the last 2-3 months, and wanted to jot down my thoughts on what works, what doesn’t (yet?), and what the future might look like. If you are curious about AI for programming, or have been skeptical in the past, if “AI slop” is the first thing that comes to mind, this post will show you some ways that AI can be really helpful. Certain tasks have been completely transformed. Notice, I said “some”, not “all”! But it is a lot.

I’ve just released repo-review 1.0 with a huge update to the WebApp, along with some other solid improvements in speed, simplicity, and stability. Repo-review’s two most popular plugins, sp-repo-review and validate-pyproject, can take full advantage of the new asynchronous fetching mechanism. And if you use the upcoming Python 3.15, the CLI is more responsive than ever thanks to lazy loading!

Python 3.15a7, which is now just a uv python install 3.15 away on all major platforms, has lazy imports! This exciting feature, proposed in PEP 810, promises to make CLI applications faster (especially when using flags like --help), and could make a lot of large code with lots of imports that don’t always get used faster too. Unlike the earlier, failed attempt, this requires libraries to put in some work. I’ve developed a helper tool to make it easy; I’d like to cover what lazy imports are and how to use my tool. Since this is the first library that I used AI heavily in developing, the second half of the post will cover how my experience with AI for a task like this went.

TL;DR: run uvx flake8-lazy --apply to make your code magically faster on Python 3.15!

I’ve just released boost-histogram 1.7 and hist 2.10, with a major new feature and a big typing improvement! I’d like to quickly outline what’s new here. Python 3.10+ is now required.

Along with a pip (and now packaging) maintainer, Damian Shaw, I have been working on making packaging, the library behind almost all packaging related tools, faster at reading versions and specifiers, something tools like pip have to do thousands of times during resolution. Using Python 3.15’s new statistical profiler and metadata from every package ever uploaded to PyPI, I measured and improved core Packaging constructs while keeping the code readable and simple. Reading in Versions can be up to 2x faster and SpecifierSets can be up to 3x faster in packaging 26.0, now released! Other operations have been optimized, as well, up to 5x in some cases. See the announcement and release notes too; this post will focus on the performance work only.

UHI 1.0 is out, with a major new feature: a new histogram serialization spec! This spec supports multiple formats (HDF5, zip, and JSON initially), and can be supported by multiple libraries (Boost-histogram/hist initially). There’s also a new test suite helper for libraries targeting the UHI indexing spec.

Pybind11 3.0 has been released! I would like to highlight some of the key changes below; be sure to check out the changelog and upgrade guide for more information! This release includes an ABI bump, the first required bump in many years on Unix (Windows has had required bumps more often). This release contains the multi-year smart-holder branch, multi-phase init and subinterpreter support, py::native_enum, an interface to warnings, typing improvements, and more. CMake now defaults to FindPython mode.

Support for Python 3.14, 3.14t, GraalPy, PyPy 3.11, and iOS have been added, while legacy support for Python 3.7, PyPy 3.8/3.9, and CMake <3.15 has been removed. Most deprecated features have been kept for this release, but anything producing a warning in 3.0 may be removed in a future 3.x version.