# pypy / pypy / doc / release-1.0.0.rst

 David Malcolm 1e46012 2011-03-14   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 ========================================== PyPy 1.0: JIT compilers for free and more ========================================== Welcome to the PyPy 1.0 release - a milestone integrating the results of four years of research, engineering, management and sprinting efforts, concluding the 28 months phase of EU co-funding! Although still not mature enough for general use, PyPy 1.0 materializes for the first time the full extent of our original vision: - A flexible Python interpreter, written in "RPython": - Mostly unaware of threading, memory and lower-level target platform aspects. - Showcasing advanced interpreter features and prototypes. - Passing core CPython regression tests, translatable to C, LLVM and .NET. - An advanced framework to translate such interpreters and programs: - That performs whole type-inference on RPython programs. - Can weave in threading, memory and target platform aspects. - Has low level (C, LLVM) and high level (CLI, Java, JavaScript) backends. - A **Just-In-Time Compiler generator** able to **automatically** enhance the low level versions of our Python interpreter, leading to run-time machine code that runs algorithmic examples at speeds typical of JITs! Previous releases, particularly the 0.99.0 release from February, already highlighted features of our Python implementation and the abilities of our translation approach but the **new JIT generator** clearly marks a major research result and gives weight to our vision that one can generate efficient interpreter implementations, starting from a description in a high level language. We have prepared several entry points to help you get started: * The main entry point for JIT documentation and status: http://codespeak.net/pypy/dist/pypy/doc/jit.html * The main documentation and getting-started PyPy entry point: http://codespeak.net/pypy/dist/pypy/doc/index.html * Our online "play1" demos showcasing various Python interpreters, features (and a new way to program AJAX applications): http://play1.codespeak.net/ * Our detailed and in-depth Reports about various aspects of the project: http://codespeak.net/pypy/dist/pypy/doc/index-report.html In the next few months we are going to discuss the goals and form of the next stage of development - now more than ever depending on your feedback and contributions - and we hope you appreciate PyPy 1.0 as an interesting basis for greater things to come, as much as we do ourselves! have fun, the PyPy release team, Samuele Pedroni, Armin Rigo, Holger Krekel, Michael Hudson, Carl Friedrich Bolz, Antonio Cuni, Anders Chrigstroem, Guido Wesdorp Maciej Fijalkowski, Alexandre Fayolle and many others: http://codespeak.net/pypy/dist/pypy/doc/contributor.html What is PyPy? ================================ Technically, PyPy is both a Python interpreter implementation and an advanced compiler, or more precisely a framework for implementing dynamic languages and generating virtual machines for them. The framework allows for alternative frontends and for alternative backends, currently C, LLVM and .NET. For our main target "C", we can can "mix in" different garbage collectors and threading models, including micro-threads aka "Stackless". The inherent complexity that arises from this ambitious approach is mostly kept away from the Python interpreter implementation, our main frontend. PyPy is now also a Just-In-Time compiler generator. The translation framework contains the now-integrated JIT generation technology. This depends only on a few hints added to the interpreter source and should be able to cope with the changes to the interpreter and be generally applicable to other interpreters written using the framework. Socially, PyPy is a collaborative effort of many individuals working together in a distributed and sprint-driven way since 2003. PyPy would not have gotten as far as it has without the coding, feedback and general support from numerous people. Formally, many of the current developers were involved in executing an EU contract with the goal of exploring and researching new approaches to language and compiler development and software engineering. This contract's duration is about to end this month (March 2007) and we are working and preparing the according final review which is scheduled for May 2007. For the future, we are in the process of setting up structures to help maintain conceptual integrity of the project and to discuss and deal with funding opportunities related to further PyPy sprinting and developments. See here for results of the discussion so far: http://codespeak.net/pipermail/pypy-dev/2007q1/003577.html 1.0.0 Feature highlights ============================== Here is a summary list of key features included in PyPy 1.0: - The Just-In-Time compiler generator, now capable of generating the first JIT compiler versions of our Python interpreter: http://codespeak.net/pypy/dist/pypy/doc/jit.html - More Python interpreter optimizations (a CALL_METHOD bytecode, a method cache, rope-based strings), now running benchmarks at around half of CPython's speed (without the JIT): http://codespeak.net/pypy/dist/pypy/doc/interpreter-optimizations.html - The Python interpreter can be translated to .NET and enables interactions with the CLR libraries: http://codespeak.net/pypy/dist/pypy/doc/cli-backend.html http://codespeak.net/pypy/dist/pypy/doc/clr-module.html - Aspect Oriented Programming facilities (based on mutating the Abstract Syntax Tree): http://codespeak.net/pypy/dist/pypy/doc/aspect_oriented_programming.html http://codespeak.net/pypy/extradoc/eu-report/D10.1_Aspect_Oriented_Programming_in_PyPy-2007-03-22.pdf - The JavaScript backend has evolved to a point where it can be used to write AJAX web applications with it. This is still an experimental technique, though. For demo applications which also showcase various generated Python and PROLOG interpreters, see: http://play1.codespeak.net/ - Proxying object spaces and features of our Python interpreter: - Tainting: a 270-line proxy object space tracking and boxing sensitive information within an application. - Transparent proxies: allow the customization of both application and builtin objects from application level code. Now featuring an initial support module (tputil.py) for working with transparent proxies. For a detailed description and discussion of high level backends and Python interpreter features, please see our extensive "D12" report: http://codespeak.net/pypy/extradoc/eu-report/D12.1_H-L-Backends_and_Feature_Prototypes-2007-03-22.pdf Funding partners and organizations ===================================================== PyPy development and activities happen as an open source project and with the support of a consortium partially funded by a 28 month European Union IST research grant for the period from December 2004 to March 2007. The full partners of that consortium are: Heinrich-Heine University (Germany), Open End (Sweden) merlinux GmbH (Germany), tismerysoft GmbH (Germany) Logilab Paris (France), DFKI GmbH (Germany) ChangeMaker (Sweden), Impara (Germany) 
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