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| Please refer to [[http://codespeak.net/pypy|the PyPy home page]] for more information about this upcoming Python implementation. |
Please refer to the [[http://pypy.org|PyPy home page]] and [[http://codespeak.net/pypy|development site]] for more information about this Python implementation. |
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| PyPy 1.0 was released on 27/03/2007 http://codespeak.net/pypy/dist/pypy/doc/release-1.0.0.html | [[http://codespeak.net/pypy/dist/pypy/doc/release-1.0.0.html|PyPy 1.0]] was released on 27/03/2007 |
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| It includes a JIT compiler, stackless-like functionality, uses the [[http://www.hpl.hp.com/personal/Hans_Boehm/gc/|Boehm garbage collector]] and has whole lot of "backends" - C, LLVM, JavaScript, CLI, Java. | It includes a JIT compiler, stackless-like functionality, uses the [[http://www.hpl.hp.com/personal/Hans_Boehm/gc/|Boehm garbage collector]] and has whole lot of "backends" - C, LLVM, !JavaScript, CLI, Java. |
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| PyPy 1.1 was released on 28/04/2009 http://codespeak.net/pypy/dist/pypy/doc/release-1.1.0.html | [[http://codespeak.net/pypy/dist/pypy/doc/release-1.1.0.html|PyPy 1.1]] was released on 28/04/2009 |
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[[http://codespeak.net/pypy/dist/pypy/doc/release-1.2.0.html|PyPy 1.2]] was released on 12/03/2010 The emphasis of this release is performance, with the JIT-enabled implementation known to outperform CPython on some real-world applications and benchmarks. |
PyPy
PyPy is a Python implementation in Python. Yes, it can interpret itself!
Please refer to the PyPy home page and development site for more information about this Python implementation.
PyPy 1.0 was released on 27/03/2007
It includes a JIT compiler, stackless-like functionality, uses the Boehm garbage collector and has whole lot of "backends" - C, LLVM, JavaScript, CLI, Java.
PyPy 1.1 was released on 28/04/2009
Some of the backends supported in 1.0 (namely The LLVM and the JS backends) have been dropped "because they were unmaintained and/or buggy". The old JIT has also been dropped in favor of a new one that is under active development.
PyPy 1.2 was released on 12/03/2010
The emphasis of this release is performance, with the JIT-enabled implementation known to outperform CPython on some real-world applications and benchmarks.