PyPy 1.1: Compatibility & Consolidation
Welcome to the PyPy 1.1 release - the first release after the end of EU
funding. This release focuses on making PyPy's Python interpreter more
compatible with CPython (currently CPython 2.5) and on making the
interpreter more stable and bug-free.
PyPy's Getting Started lives at:
Highlights of This Release
- More of CPython's standard library extension modules are supported,
among them ctypes, sqlite3, csv, and many more. Most of these extension
modules are fully supported under Windows as well.
- Through a large number of tweaks, performance has been improved by
10%-50% since the 1.0 release. The Python interpreter is now between
0.8-2x (and in some corner case 3-4x) slower than CPython. A large
part of these speed-ups come from our new generational garbage
- Our Python interpreter now supports distutils as well as
easy_install for pure-Python modules.
- We have tested PyPy with a number of third-party libraries. PyPy can
run now: Django, Pylons, BitTorrent, Twisted, SymPy, Pyglet, Nevow,
- A buildbot was set up to run the various tests that PyPy is using
nightly on Windows and Linux machines:
- Sandboxing support: It is possible to translate the Python
interpreter in a special way so that the result is fully sandboxed.
- The ``clr`` module was greatly improved. This module is used to
interface with .NET libraries when translating the Python
interpreter to the CLI.
- Stackless improvements: PyPy's ``stackless`` module is now more
complete. We added channel preferences which change details of the
scheduling semantics. In addition, the pickling of tasklets has been
improved to work in more cases.
- Classic classes are enabled by default now. In addition, they have
been greatly optimized and debugged:
- PyPy's Python interpreter can be translated to Java bytecode now to
produce a pypy-jvm. At the moment there is no integration with
Java libraries yet, so this is not really useful.
- We added cross-compilation machinery to our translation toolchain to
make it possible to cross-compile our Python interpreter to Nokia's
- Some effort was spent to make the Python interpreter more
memory-efficient. This includes the implementation of a mark-compact
GC which uses less memory than other GCs during collection.
Additionally there were various optimizations that make Python
objects smaller, e.g. class instances are often only 50% of the size
- The support for the trace hook in the Python interpreter was
improved to be able to trace the execution of builtin functions and
methods. With this, we implemented the ``_lsprof`` module, which is
the core of the ``cProfile`` module.
- A number of rarely used features of PyPy were removed since the previous
release because they were unmaintained and/or buggy. Those are: The
LLVM and the JS backends, the aspect-oriented programming features,
the logic object space, the extension compiler and the first
incarnation of the JIT generator. The new JIT generator is in active
development, but not included in the release.
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 framework allows for alternative frontends and for alternative
backends, currently C, Java and .NET. For our main target "C", we can
"mix in" different garbage collectors and threading models,
including micro-threads aka "Stackless". The inherent complexity that
arises from this ambitious approach is mostly kept away from the Python
interpreter implementation, our main frontend.
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, [in alphabetical order]
Amaury Forgeot d'Arc, Anders Hammerquist, Antonio Cuni, Armin Rigo,
Carl Friedrich Bolz, Christian Tismer, Holger Krekel,
Maciek Fijalkowski, Samuele Pedroni
and many others: