PyPy v7.3.4: release of python 2.7 and 3.7
PyPy v7.3.4: release of python 2.7 and 3.7
The PyPy team is proud to release the version 7.3.4 of PyPy, which includes two different interpreters:
PyPy2.7, which is an interpreter supporting the syntax and the features of Python 2.7 including the stdlib for CPython 2.7.18+ (the
+is for backported security updates)
PyPy3.7, which is an interpreter supporting the syntax and the features of Python 3.7, including the stdlib for CPython 3.7.10. We no longer refer to this as beta-quality as the last incompatibilities with CPython (in the
remodule) have been fixed.
We are no longer releasing a Python3.6 version, as we focus on updating to Python 3.8. We have begun streaming the advances towards this goal on Saturday evenings European time on https://www.twitch.tv/pypyproject. If Python3.6 is important to you, please reach out as we could offer sponsored longer term support.
The two interpreters are based on much the same codebase, thus the multiple release. This is a micro release, all APIs are compatible with the other 7.3 releases. Highlights of the release include binary Windows 64 support, faster numerical instance fields, and a preliminary HPy backend.
A new contributor (Ondrej Baranovič - thanks!) took us up on the challenge to get windows 64-bit support. The work has been merged and for the first time we are releasing a 64-bit Windows binary package.
The release contains the biggest change to PyPy's implementation of the
instances of user-defined classes in many years. The optimization was
motivated by the report of performance problems running a numerical particle
emulation. We implemented an optimization that stores
instance fields in an unboxed way, as long as these fields are type-stable
(meaning that the same field always stores the same type, using the principle
of type freezing). This gives significant performance improvements on
numerical pure-Python code, and other code where instances store many integers
or floating point numbers.
There were also a number of optimizations for methods around strings and bytes, following user reported performance problems. If you are unhappy with PyPy's performance on some code of yours, please report an issue!
A major new feature is prelminary support for the Universal mode of HPy: a
new way of writing c-extension modules to totally encapsulate
The goal, as laid out in the HPy documentation and recent HPy blog post,
is to enable a migration path
for c-extension authors who wish their code to be performant on alternative
interpreters like GraalPython (written on top of the Java virtual machine),
RustPython, and PyPy. Thanks to Oracle and IBM for sponsoring work on HPy.
Support for the vmprof statistical profiler has been extended to ARM64 via a built-in backend.
Several issues exposed in the 7.3.3 release were fixed. Many of them came from the great work ongoing to ship PyPy-compatible binary packages in conda-forge. A big shout out to them for taking this on.
Development of PyPy takes place on https://foss.heptapod.net/pypy/pypy. We have seen an increase in the number of drive-by contributors who are able to use gitlab + mercurial to create merge requests.
The CFFI backend has been updated to version 1.14.5 and the cppyy backend to 1.14.2. We recommend using CFFI rather than C-extensions to interact with C, and using cppyy for performant wrapping of C++ code for Python.
As always, we strongly recommend updating to the latest versions. Many fixes are the direct result of end-user bug reports, so please continue reporting issues as they crop up.
You can find links to download the v7.3.4 releases here:
We would like to thank our donors for the continued support of the PyPy project. If PyPy is not quite good enough for your needs, we are available for direct consulting work. If PyPy is helping you out, we would love to hear about it and encourage submissions to our renovated blog site via a pull request to https://github.com/pypy/pypy.org
We would also like to thank our contributors and encourage new people to join the project. PyPy has many layers and we need help with all of them: PyPy and RPython documentation improvements, tweaking popular modules to run on PyPy, or general help with making RPython's JIT even better. Since the previous release, we have accepted contributions from 10 new contributors, thanks for pitching in, and welcome to the project!
If you are a python library maintainer and use C-extensions, please consider making a cffi / cppyy version of your library that would be performant on PyPy. In any case both cibuildwheel and the multibuild system support building wheels for PyPy.
What is PyPy?
PyPy is a Python interpreter, a drop-in replacement for CPython 2.7, 3.7, and soon 3.8. It's fast (PyPy and CPython 3.7.4 performance comparison) due to its integrated tracing JIT compiler.
We also welcome developers of other dynamic languages to see what RPython can do for them.
This PyPy release supports:
x86 machines on most common operating systems (Linux 32/64 bits, Mac OS X 64 bits, Windows 32/64 bits, OpenBSD, FreeBSD)
big- and little-endian variants of PPC64 running Linux,
s390x running Linux
64-bit ARM machines running Linux.
PyPy does support ARM 32 bit processors, but does not release binaries.
What else is new?
For more information about the 7.3.4 release, see the full changelog.
Please update, and continue to help us make PyPy better.
Cheers, The PyPy team