PyPy 2.5 - XXXXXX

We’re pleased to announce PyPy 2.5, which contains significant performance enhancements and bug fixes.

You can download the PyPy 2.5.0 release here:

We would like to thank our donors for the continued support of the PyPy project, and for those who donate to our three sub-projects, as well as our volunteers and contributors (10 new commiters joined PyPy since the last release). We’ve shown quite a bit of progress, but we’re slowly running out of funds. Please consider donating more, or even better convince your employer to donate, so we can finish those projects! The three sub-projects are:

  • Py3k (supporting Python 3.x): We have released a Python 3.2.5 compatible version

    we call PyPy3 2.4.0, and are working toward a Python 3.3 compatible version

  • STM (software transactional memory): We have released a first working version, and continue to try out new promising paths of achieving a fast multithreaded Python

  • NumPy which requires installation of our fork of upstream numpy, available on bitbucket

What is PyPy?

PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython 2.7. It’s fast (pypy and cpython 2.7.x performance comparison) due to its integrated tracing JIT compiler.

This release supports x86 machines on most common operating systems (Linux 32/64, Mac OS X 64, Windows, and OpenBSD), as well as newer ARM hardware (ARMv6 or ARMv7, with VFPv3) running Linux.

While we support 32 bit python on Windows, work on the native Windows 64 bit python is still stalling, we would welcome a volunteer to handle that.

Highlights

  • The past months have seen pypy mature and grow, as rpython becomes the goto solution for writing fast dynamic language interpreters. Our separation of rpython and the python interpreter PyPy is now much clearer in the documentation .
  • We have improved warmup time as well as jitted code performance: more than 10% compared to pypy-2.4.0, due to internal cleanup and gc nursery improvements.
  • Our integrated numpy support gained much of the GenericUfunc api in order to support the lapack/blas linalg module of numpy. This dovetails with work in the pypy/numpy repository to support linalg both through the (slower) cpyext capi interface and also via (the faster) pure python cffi interface, using an extended frompyfunc() api.
  • Dictionaries are now ordered by default, see the blog post
  • Issues reported with our previous release were fixed after reports from users on our issue tracker at https://bitbucket.org/pypy/pypy/issues or on IRC at #pypy. Here is a summary of some of the user-facing changes; for more information see whats-new:
  • Our nightly translations use –shared by default, including on OS/X and linux
  • We now more carefully handle errno (and GetLastError, WSAGetLastError) tying the handlers as close as possible to the external function call, in non-jitted as well as jitted code.
  • Many issues were resolved since the 2.4.0 release in September 2014

We have further improvements on the way: rpython file handling, finishing numpy linalg compatibility, numpy object dtypes, a better profiler, as well as support for Python stdlib 2.7.9.

Please try it out and let us know what you think. We especially welcome success stories, we know you are using PyPy, please tell us about it!

Cheers

The PyPy Team

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