PyPy 1.5: Catching Up¶
We’re pleased to announce the 1.5 release of PyPy. This release updates PyPy with the features of CPython 2.7.1, including the standard library. Thus all the features of CPython 2.6 and CPython 2.7 are now supported. It also contains additional performance improvements. You can download it here:
What is PyPy?¶
PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython 2.7.1. It’s fast (pypy 1.5 and cpython 2.6.2 performance comparison) due to its integrated tracing JIT compiler.
This release includes the features of CPython 2.6 and 2.7. It also includes a large number of small improvements to the tracing JIT compiler. It supports Intel machines running Linux 32/64 or Mac OS X. Windows is beta (it roughly works but a lot of small issues have not been fixed so far). Windows 64 is not yet supported.
Numerous speed achievements are described on our blog. Normalized speed charts comparing pypy 1.5 and pypy 1.4 as well as pypy 1.5 and cpython 2.6.2 are available on our benchmark website. The speed improvement over 1.4 seems to be around 25% on average.
- The largest change in PyPy’s tracing JIT is adding support for loop invariant code motion, which was mostly done by Håkan Ardö. This feature improves the performance of tight loops doing numerical calculations.
- The CPython extension module API has been improved and now supports many more extensions.
- These changes make it possible to support Tkinter and IDLE.
- The cProfile profiler is now working with the JIT. However, it skews the performance in unstudied ways. Therefore it is not yet usable to analyze subtle performance problems (the same is true for CPython of course).
- There is an external fork which includes an RPython version of the
postgresql. However, there are no prebuilt binaries for this.
- Our developer documentation was moved to Sphinx and cleaned up. (click ‘Dev Site’ on https://pypy.org/ .)
- and many small things :-)
Carl Friedrich Bolz, Laura Creighton, Antonio Cuni, Maciej Fijalkowski, Amaury Forgeot d’Arc, Alex Gaynor, Armin Rigo and the PyPy team