On Fri, Nov 23, 2012 at 4:51 PM, Phyo Arkar <[email protected]> wrote: > 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!
No, it works on ARM linux. I have no idea what it takes to make it work on Android (hopefully not much) > > 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 <[email protected]> > 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 >> [email protected] >> http://mail.python.org/mailman/listinfo/pypy-dev > > _______________________________________________ pypy-dev mailing list [email protected] http://mail.python.org/mailman/listinfo/pypy-dev
