[pypy-dev] PyPy 2.0 beta 1 released

[Phyo Arkar]

Hey ,
ARM Build! thats mean we can run Pypy in android now right?
I am building my own Python for Android with required dependencies , i am
gonna test pypy on android too!

Thanks , good job pypy team!

When do you think numpypy and pypy c extension is complete enought to
support matplotlib/scipy/pylab kit (they have a lot of other
C Dependencies ..)

Thanks!


On Thu, Nov 22, 2012 at 6:24 PM, Maciej Fijalkowski <fijall at gmail.com>wrote:

> We're pleased to announce the 2.0 beta 1 release of PyPy. This release is
> not a typical beta, in a sense the stability is the same or better than 1.9
> and can be used in production. It does however include a few performance
> regressions documented below that don't allow us to label is as 2.0 final.
> (It also contains many performance improvements.)
>
> The main features of this release are support for ARM processor and
> compatibility with CFFI. It also includes
> numerous improvements to the numpy in pypy effort, cpyext and performance.
>
> You can download the PyPy 2.0 beta 1 release here:
>
>     http://pypy.org/download.html
>
> What is PyPy?
> =============
>
> PyPy is a very compliant Python interpreter, almost a drop-in replacement
> for
> CPython 2.7.3. It's fast (`pypy 2.0 beta 1 and cpython 2.7.3`_
> performance comparison) due to its integrated tracing JIT compiler.
>
> This release supports x86 machines running Linux 32/64, Mac OS X 64 or
> Windows 32. It also supports ARM machines running Linux.
> Windows 64 work is still stalling, we would welcome a volunteer
> to handle that.
>
> .. _`pypy 2.0 beta 1 and cpython 2.7.3`: http://bit.ly/USXqpP
>
> How to use PyPy?
> ================
>
> We suggest using PyPy from a `virtualenv`_. Once you have a virtualenv
> installed, you can follow instructions from `pypy documentation`_ on how
> to proceed. This document also covers other `installation schemes`_.
>
> .. _`pypy documentation`:
>
> http://doc.pypy.org/en/latest/getting-started.html#installing-using-virtualenv
> .. _`virtualenv`: http://www.virtualenv.org/en/latest/
> .. _`installation schemes`:
> http://doc.pypy.org/en/latest/getting-started.html#installing-pypy
> .. _`PyPy and pip`:
> http://doc.pypy.org/en/latest/getting-started.html#installing-pypy
>
> Regressions
> ===========
>
> Reasons why this is not PyPy 2.0:
>
> * the ``ctypes`` fast path is now slower than it used to be. In PyPy
>   1.9 ``ctypes`` was either incredibly faster or slower than CPython
> depending whether
>   you hit the fast path or not. Right now it's usually simply slower. We're
>   probably going to rewrite ``ctypes`` using ``cffi``, which will make it
>   universally faster.
>
> * ``cffi`` (an alternative to interfacing with C code) is very fast, but
>   it is missing one optimization that will make it as fast as a native
>   call from C.
>
> * ``numpypy`` lazy computation was disabled for the sake of simplicity.
>   We should reenable this for the final 2.0 release.
>
> Highlights
> ==========
>
> * ``cffi`` is officially supported by PyPy. You can install it normally by
>   using ``pip install cffi`` once you have installed `PyPy and pip`_.
>   The corresponding ``0.4`` version of ``cffi`` has been released.
>
> * ARM is now an officially supported processor architecture.
>   PyPy now work on soft-float ARM/Linux builds.  Currently ARM processors
>   supporting the ARMv7 and later ISA that include a floating-point unit are
>   supported.
>
> * This release contains the latest Python standard library 2.7.3 and is
> fully
>   compatible with Python 2.7.3.
>
> * It does not however contain hash randomization, since the solution
> present
>   in CPython is not solving the problem anyway. The reason can be
>   found on the `CPython issue tracker`_.
>
> * ``gc.get_referrers()`` is now faster.
>
> * Various numpy improvements. The list includes:
>
>   * axis argument support in many places
>
>   * full support for fancy indexing
>
>   * ``complex128`` and ``complex64`` dtypes
>
> * `JIT hooks`_ are now a powerful tool to introspect the JITting process
> that
>   PyPy performs.
>
> * ``**kwds`` usage is much faster in the typical scenario
>
> * operations on ``long`` objects are now as fast as in CPython (from
>   roughly 2x slower)
>
> * We now have special strategies for ``dict``/``set``/``list`` which
> contain
>   unicode strings, which means that now such collections will be both
> faster
>   and more compact.
>
> .. _`cpython issue tracker`: http://bugs.python.org/issue14621
> .. _`jit hooks`: http://doc.pypy.org/en/latest/jit-hooks.html
>
> Things we're working on
> =======================
>
> There are a few things that did not make it to the 2.0 beta 1, which
> are being actively worked on. Greenlets support in the JIT is one
> that we would like to have before 2.0 final. Two important items that
> will not make it to 2.0, but are being actively worked on, are:
>
> * Faster JIT warmup time.
>
> * Software Transactional Memory.
>
> Cheers,
> Maciej Fijalkowski, Armin Rigo and the PyPy team
> _______________________________________________
> pypy-dev mailing list
> pypy-dev at python.org
> http://mail.python.org/mailman/listinfo/pypy-dev
>
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