Exploring the Concept of Lifetimes in Rust and Their Significance in Programming

There’s huge pressure on Python at the moment to get faster, ideally without changing at all. One increasingly–popular way of achieving that impossible task is to push the performance critical code down into C, C++, or Rust. And this week we’re focussing on the Python route, as we take a look at PyO3.

David Hewitt’s the principal committer to PyO3, and he joins us to go through the easy parts, the hard parts, and the works in progress, giving us an insight into how Python and Rust work under the hood, and quite how much work it takes to make them work as one.

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PyO3 User Guide: https://pyo3.rs/v0.22.0/

PyO3 on Github: https://github.com/PyO3/pyo3

Polars: https://pola.rs/

Tokio: https://tokio.rs/

Trio: https://trio.readthedocs.io/

Robyn: https://github.com/sparckles/Robyn

Faster CPython: https://github.com/faster-cpython

Maturin: https://www.maturin.rs/

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David on Mastodon: https://fosstodon.org/@davidhewitt

David on Twitter: https://x.com/davidhewittdev

Kris on Mastodon: http://mastodon.social/@krisajenkins

Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

Kris on Twitter: https://x.com/krisajenkins