Tuesday, August 17, 2010

EuroPython 2010 Videos available

Hi all,

the videos of the talks from EuroPython 2010 are now available on blip.tv: in particular, there are the three videos of the PyPy talk.

Part 1: What's news in PyPy 1.2 and 1.3 (by Antonio Cuni)

Part 2: Just in Time compilation (by Armin Rigo)

Part 3: cpyext (by Amaury Forgeot d'Arc)

Moreover, here is Mark Shannon's talk which compares HotPy, Unladen Swallow and PyPy:

Call for Benchmarks

As you know, a lot of PyPy's recent development effort has gone into speeding up execution of Python programs. However, an additional good property of PyPy's Python interpreter is that most objects are represented in a much more compact way than in CPython. We would like to investigate some more advanced techniques to reduce the memory usage of Python programs further.

To do this it is necessary to investigate the memory behaviour of real programs with large heaps. For speed measurements there are standard benchmarks, but for memory improvements there is nothing comparable, the memory behaviour of large programs is not that well understood. Therefore we are looking for programs that we can study and use as benchmarks.

Specifically we are looking for Python programs with the following properties:

  • large heaps of about 10MB-1GB
  • should have non-trivial runtime as well (in the range of a few seconds), to judge the speed impact of optimizations
  • ideally pure-Python programs that don't use extension modules so that they run under both CPython and PyPy (this is optional, but makes my life much easier).

We are also rather interested in programs that do a lot of string/unicode processing.

We would be grateful for all ideas. Telling us about a program also has the advantage that we will work on optimizing PyPy for it :-).

Monday, August 2, 2010


This weekend I delivered a talk at PyOhio (an annual conference in Columbus, OH, USA) on PyPy and Unladen Swallow. The talk covered reasons that Python, the language, is hard to optimize, why CPython is slow, and a few optimizations that PyPy and Unladen Swallow have implemented. The slides from my talk are online, and the talk was recorded so a video will follow. I gave a similar talk to ChiPy (the Chicago Python user group), which was also recorded and the video is available. Both audiences were excited about the futures for PyPy and Unladen Swallow, and for the future of a faster Python.


Using virtualenv with PyPy

Thanks to the work that was recently done on the sys-prefix branch, it is now possible to use virtualenv with PyPy.

To try it, you need:

  • a recent version of PyPy: PyPy 1.3 does not contain the necessary logic to work with virtualenv, so you need a more recent PyPy from subversion trunk. You can either build it by yourself or download one of our precompiled nightly builds
  • a copy of virtualenv-pypy: this is a fork of virtualenv that contains all the patches needed to work with PyPy, and hopefully will be merged back at some point. It should be totally compatible with the official version of virtualenv, so it is safe to use it even to create non-PyPy environments. If you notice some weird behavior that does not happen with the standard virtualenv, please let us know.

The directory layout has been redesigned in a way that it is possible to use virtualenv to install a PyPy both from a precompiled tarball or from an svn checkout:

# from a tarball
$ virtualenv -p /opt/pypy-c-jit-76426-linux/bin/pypy my-pypy-env

# from the svn checkout
$ virtualenv -p /path/to/pypy-trunk/pypy/translator/goal/pypy-c my-pypy-env

Once the environment has been created, you can enter it as usual. Note that bin/python is now a symlink to bin/pypy.

Enjoy it :-)