PyPy 1.2: Just-in-Time Compilation

Welcome to the PyPy 1.2 release. The highlight of this release is to be the first that ships with a Just-in-Time compiler that is known to be faster than CPython (and unladen swallow) on some real-world applications (or the best benchmarks we could get for them). The main theme for the 1.2 release is speed.

Main site:

The JIT is stable and we don’t observe crashes. Nevertheless we would recommend you to treat it as beta software and as a way to try out the JIT to see how it works for you.

Highlights of This Release

  • The JIT compiler.
  • Various interpreter optimizations that improve performance as well as help save memory.
  • Introducing a new PyPy website at , made by tav and improved by the PyPy team.
  • Introducing , a new service that monitors our performance nightly, made by Miquel Torres.
  • There will be ubuntu packages on “PyPy’s PPA” made by Bartosz Skowron; however various troubles prevented us from having them as of now.

Known JIT problems (or why you should consider this beta software):

  • The only supported platform is 32bit x86 for now, we’re looking for help with other platforms.
  • It is still memory-hungry. There is no limit on the amount of RAM that the assembler can consume; it is thus possible (although unlikely) that the assembler ends up using unreasonable amounts of memory.

If you want to try PyPy, go to the “download page” on our excellent new site at and find the binary for your platform. If the binary does not work (e.g. on Linux, because of different versions of external .so dependencies), or if your platform is not supported, you can try building from the source.

What is PyPy?

Technically, PyPy is both a Python interpreter implementation and an advanced compiler, or more precisely a framework for implementing dynamic languages and generating virtual machines for them. The focus of this release is the introduction of a new transformation, the JIT Compiler Generator, and its application to the Python interpreter.

Socially, PyPy is a collaborative effort of many individuals working together in a distributed and sprint-driven way since 2003. PyPy would not have gotten as far as it has without the coding, feedback and general support from numerous people.

The PyPy release team,
Armin Rigo, Maciej Fijalkowski and Amaury Forgeot d’Arc
Together with
Antonio Cuni, Carl Friedrich Bolz, Holger Krekel and Samuele Pedroni
and many others: