#544: Wheel Next + Packaging PEPs
When you pip install a package with compiled code, the wheel you get is built for CPU features from 2009. Want newer optimizations like AVX2? Your installer has no way to ask for them. GPU support? You're on your own configuring special index URLs. The result is fat binaries, nearly gigabyte-sized wheels, and install pages that read like puzzle books. A coalition from NVIDIA, Astral, and QuanSight has been working on Wheel Next: A set of PEPs that let packages declare what hardware they need and let installers like uv pick the right build automatically. Just uv pip install torch and it works. I sit down with Jonathan Dekhtiar from NVIDIA, Ralf Gommers from Quansight and the NumPy and SciPy teams, and Charlie Marsh, founder of Astral and creator of uv, to dig into all of it. Episode sponsors Sentry Error Monitoring, Code talkpython26 Temporal Talk Python Courses Links from the show Guests Charlie Marsh: github.com Ralf Gommers: github.com Jonathan Dekhtiar: github.com CPU dispatcher: numpy.org build options: numpy.org Red Hat RHEL: www.redhat.com Red Hat RHEL AI: www.redhat.com RedHats presentation: wheelnext.dev CUDA release: developer.nvidia.com requires a PEP: discuss.python.org WheelNext: wheelnext.dev Github repo: github.com PEP 817: peps.python.org PEP 825: discuss.python.org uv: docs.astral.sh A variant-enabled build of uv: astral.sh pyx: astral.sh pypackaging-native: pypackaging-native.github.io PEP 784: peps.python.org Watch this episode on YouTube: youtube.com Episode #544 deep-dive: talkpython.fm/544 Episode transcripts: talkpython.fm Theme Song: Developer Rap 🥁 Served in a Flask 🎸: talkpython.fm/flasksong ---== Don't be a stranger ==--- YouTube: youtube.com/@talkpython Bluesky: @talkpython.fm Mastodon: @talkpython@fosstodon.org X.com: @talkpython Michael on Bluesky: @mkennedy.codes Michael on Mastodon: @mkennedy@fosstodon.org Michael on X.com: @mkennedy