Clearly, PyPy is more than a just faster alternative to the standard Python implementation CPython with a JIT and an experimental Software transactional memory implementation. Some people even use it to implement their own programming languages.

We took the opportunity to catch the two core members Armin and Maciej of the PyPy project at a Sprint in Leipzig. They talk about the project, what they achieved so far, what's boiling at the moment, and what else you can achieve with the RPython toolchain.

You will have noticed it by now, we fell back to the least common denominator English as the interview language. We applolgise in advance for the restricted recording environment.

As a side note, this podcast now is also available via bittorrent from Bitlove.org.

Shownotes:

00:00:45 Intro of our special guests Armin and Maciej

00:04:33 CRE088 Python und PyPy

00:07:15 Speed gain and benchmarking

00:08:40 Codespeed / speed.pypy.org

00:09:15 PyPy project, contributing

00:16:13 Development workflow

00:20:25 PyPy in detail: the components and features

00:24:00 PyPy can be faster than C ;-)

00:26:15 What happens when you execute pypy or the Toolchain

00:30:27 A little bit about the JIT

00:33:50 RAM consumption

00:43:00 Sandboxing

00:45:33 Software and Hardware Transactional Memory (STM and HTM)/ Automatic Mutual Exclusion

01:01:17 What is the Global Interpreter Lock and Stackless?

01:05:50 How to support PyPy or sub projects?

01:08:10 Who uses PyPy?

01:08:10 Who uses PyPy? Which Python projects support PyPy?

01:11:10 How to file bug reports?

01:14:36 Outlook.