#544: Wheel Next + Packaging PEPs

About this episode

The episode discusses Wheel Next and packaging PEPs aimed at improving package installations for modern hardware.

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.

People in this episode

Host: Michael Kennedy

Guests: Jonathan Dekhtiar, Ralf Gommers, Charlie Marsh

Topics covered

• packaging
• Python
• wheel format
• hardware optimization
• PEPs
• GPU support

Keywords

• wheel
• packaging
• PEPs
• AVX2
• GPU support
• Python
• installation

Mentioned in this episode

Organizations: NVIDIA, Quansight, Astral, NumPy, SciPy

Products: torch, uv

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