On Fri, Feb 10, 2012 at 5:44 PM, Maciej Fijalkowski <[email protected]>wrote:
> ============================ > PyPy 1.8 - business as usual > ============================ > > We're pleased to announce the 1.8 release of PyPy. As habitual this > release brings a lot of bugfixes, together with performance and memory > improvements over the 1.7 release. The main highlight of the release > is the introduction of `list strategies`_ which makes homogenous lists > more efficient both in terms of performance and memory. This release > also upgrades us from Python 2.7.1 compatibility to 2.7.2. Otherwise > it's "business as usual" in the sense that performance improved > roughly 10% on average since the previous release. > > you can download the PyPy 1.8 release here: > > http://pypy.org/download.html > > .. _`list strategies`: > > http://morepypy.blogspot.com/2011/10/more-compact-lists-with-list-strategies.html > > What is PyPy? > ============= > > PyPy is a very compliant Python interpreter, almost a drop-in replacement > for > CPython 2.7. It's fast (`pypy 1.8 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 has been stalled, we would welcome a volunteer > to handle that. > > .. _`pypy 1.8 and cpython 2.7.1`: http://speed.pypy.org > > > Highlights > ========== > > * List strategies. Now lists that contain only ints or only floats should > be as efficient as storing them in a binary-packed array. It also improves > the JIT performance in places that use such lists. There are also special > strategies for unicode and string lists. > > * As usual, numerous performance improvements. There are many examples > of python constructs that now should be faster; too many to list them. > > * Bugfixes and compatibility fixes with CPython. > > * Windows fixes. > > * NumPy effort progress; for the exact list of things that have been done, > consult the `numpy status page`_. A tentative list of things that has > been done: > > * multi dimensional arrays > > * various sizes of dtypes > > * a lot of ufuncs > > * a lot of other minor changes > > Right now the `numpy` module is available under both `numpy` and `numpypy` > names. However, because it's incomplete, you have to `import numpypy` > first > before doing any imports from `numpy`. > > * New JIT hooks that allow you to hook into the JIT process from your > python > program. There is a `brief overview`_ of what they offer. > > * Standard library upgrade from 2.7.1 to 2.7.2. > > Ongoing work > ============ > > As usual, there is quite a bit of ongoing work that either didn't make it > to > the release or is not ready yet. Highlights include: > > * Non-x86 backends for the JIT: ARMv7 (almost ready) and PPC64 (in > progress) > > * Specialized type instances - allocate instances as efficient as C > structs, > including type specialization > > * More numpy work > > * Since the last release there was a significant breakthrough in PyPy's > fundraising. We now have enough funds to work on first stages of > `numpypy`_ > and `py3k`_. We would like to thank again to everyone who donated. > > * It's also probably worth noting, we're considering donations for the > Software Transactional Memory project. You can read more about `our > plans`_ > > Cheers, > The PyPy Team > > .. _`brief overview`: http://doc.pypy.org/en/latest/jit-hooks.html > .. _`numpy status page`: http://buildbot.pypy.org/numpy-status/latest.html > .. _`numpy status update blog report`: > http://morepypy.blogspot.com/2012/01/numpypy-status-update.html > .. _`numpypy`: http://pypy.org/numpydonate.html > .. _`py3k`: http://pypy.org/py3donate.html > .. _`our plans`: > http://morepypy.blogspot.com/2012/01/transactional-memory-ii.html > _______________________________________________ > pypy-dev mailing list > [email protected] > http://mail.python.org/mailman/listinfo/pypy-dev > a great job...I will give a try tonight...
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