[pypy-dev] PyPy 1.7 - widening the sweet spot

Phyo Arkar phyo.arkarlwin at gmail.com
Mon Nov 21 15:08:16 CET 2011


https://bitbucket.org/pypy/pypy/downloads/pypy-1.7-win32-c.zip

can u try?>

On Mon, Nov 21, 2011 at 5:05 PM, Maciej Fijalkowski <fijall at gmail.com>wrote:

> ==================================
> PyPy 1.7 - widening the sweet spot
> ==================================
>
> We're pleased to announce the 1.7 release of PyPy. As became a habit, this
> release brings a lot of bugfixes and performance improvements over the 1.6
> release. However, unlike the previous releases, the focus has been on
> widening
> the "sweet spot" of PyPy. That is, classes of Python code that PyPy can
> greatly
> speed up should be vastly improved with this release. You can download the
> 1.7
> release here:
>
>    http://pypy.org/download.html
>
> What is PyPy?
> =============
>
> PyPy is a very compliant Python interpreter, almost a drop-in replacement
> for
> CPython 2.7. It's fast (`pypy 1.7 and cpython 2.7.1`_ performance
> comparison)
> due to its integrated tracing JIT compiler.
>
> This release supports x86 machines running Linux 32/64, Mac OS X 32/64 or
> Windows 32. Windows 64 work is ongoing, but not yet natively supported.
>
> The main topic of this release is widening the range of code which PyPy
> can greatly speed up. On average on
> our benchmark suite, PyPy 1.7 is around **30%** faster than PyPy 1.6 and up
> to **20 times** faster on some benchmarks.
>
> .. _`pypy 1.7 and cpython 2.7.1`: http://speed.pypy.org
>
>
> Highlights
> ==========
>
> * Numerous performance improvements. There are too many examples which
> python
>  constructs now should behave faster to list them.
>
> * Bugfixes and compatibility fixes with CPython.
>
> * Windows fixes.
>
> * PyPy now comes with stackless features enabled by default. However,
>  any loop using stackless features will interrupt the JIT for now, so no
> real
>  performance improvement for stackless-based programs. Contact pypy-dev for
>  info how to help on removing this restriction.
>
> * NumPy effort in PyPy was renamed numpypy. In order to try using it,
> simply
>  write::
>
>    import numpypy as numpy
>
>  at the beginning of your program. There is a huge progress on numpy in
> PyPy
>  since 1.6, the main feature being implementation of dtypes.
>
> * JSON encoder (but not decoder) has been replaced with a new one. This one
>  is written in pure Python, but is known to outperform CPython's C
> extension
>  up to **2 times** in some cases. It's about **20 times** faster than
>  the one that we had in 1.6.
>
> * The memory footprint of some of our RPython modules has been drastically
>  improved. This should impact any applications using for example
> cryptography,
>  like tornado.
>
> * There was some progress in exposing even more CPython C API via cpyext.
>
> Things that didn't make it, expect in 1.8 soon
> ==============================================
>
> There is an ongoing work, which while didn't make it to the release, is
> probably worth mentioning here. This is what you should probably expect in
> 1.8 some time soon:
>
> * Specialized list implementation. There is a branch that implements lists
> of
>  integers/floats/strings as compactly as array.array. This should
> drastically
>  improve performance/memory impact of some applications
>
> * NumPy effort is progressing forward, with multi-dimensional arrays coming
>  soon.
>
> * There are two brand new JIT assembler backends, notably for the PowerPC
> and
>  ARM processors.
>
> Fundraising
> ===========
>
> It's maybe worth mentioning that we're running fundraising campaigns for
> NumPy effort in PyPy and for Python 3 in PyPy. In case you want to see any
> of those happen faster, we urge you to donate to `numpy proposal`_ or
> `py3k proposal`_. In case you want PyPy to progress, but you trust us with
> the general direction, you can always donate to the `general pot`_.
>
> .. _`numpy proposal`: http://pypy.org/numpydonate.html
> .. _`py3k proposal`: http://pypy.org/py3donate.html
> .. _`general pot`: http://pypy.org
> _______________________________________________
> pypy-dev mailing list
> pypy-dev at python.org
> http://mail.python.org/mailman/listinfo/pypy-dev
>
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