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pkgsrc/lang/py-psyco/PLIST

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Update to 1.4, based on PR 31335 by Victor I. Additional PLIST fixes. Changes in 1.4: An interesting new optimization: instances of user-defined classes are now really supported, i.e. their attributes keep type information and are stored quite compactly in memory. However, it only works so far with instances of a new type ``psyco.compact`` (which is subclassable). The line ``from psyco.classes import *`` has the effect of turning your classes into psyco.compact subclasses, too. Changes in 1.3: Includes support for Python 2.4 (and of course still for 2.1-2.3). As always comes with a few bug fixes, including a memory leak when using the profiler. Another good news is that the built-in functions that read the local variables -- locals(), eval(), execfile(), vars(), dir(), input() -- now work correctly!
2005-10-19 03:33:16 +02:00
@comment $NetBSD: PLIST,v 1.2 2005/10/19 01:33:16 wiz Exp $
Intial import of py-psyco 1.1.1 from the pkgsrc-wip pkg by Michal Pasternak Psyco is a specializing compiler. In a few words let us first see: What you can do with it In short: run your existing Python software much faster, with no change in your source. Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like Java's, that emit machine code on the fly instead of interpreting your Python program step by step. The result is that your unmodified Python programs run faster. Benefits 2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module. Drawbacks Psyco currently uses quite a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.
2003-10-02 00:39:06 +02:00
${PYSITELIB}/psyco/__init__.py
${PYSITELIB}/psyco/__init__.pyc
${PYSITELIB}/psyco/__init__.pyo
${PYSITELIB}/psyco/_psyco.so
${PYSITELIB}/psyco/classes.py
${PYSITELIB}/psyco/classes.pyc
${PYSITELIB}/psyco/classes.pyo
${PYSITELIB}/psyco/core.py
${PYSITELIB}/psyco/core.pyc
${PYSITELIB}/psyco/core.pyo
Update to 1.4, based on PR 31335 by Victor I. Additional PLIST fixes. Changes in 1.4: An interesting new optimization: instances of user-defined classes are now really supported, i.e. their attributes keep type information and are stored quite compactly in memory. However, it only works so far with instances of a new type ``psyco.compact`` (which is subclassable). The line ``from psyco.classes import *`` has the effect of turning your classes into psyco.compact subclasses, too. Changes in 1.3: Includes support for Python 2.4 (and of course still for 2.1-2.3). As always comes with a few bug fixes, including a memory leak when using the profiler. Another good news is that the built-in functions that read the local variables -- locals(), eval(), execfile(), vars(), dir(), input() -- now work correctly!
2005-10-19 03:33:16 +02:00
${PYSITELIB}/psyco/kdictproxy.py
${PYSITELIB}/psyco/kdictproxy.pyc
${PYSITELIB}/psyco/kdictproxy.pyo
Intial import of py-psyco 1.1.1 from the pkgsrc-wip pkg by Michal Pasternak Psyco is a specializing compiler. In a few words let us first see: What you can do with it In short: run your existing Python software much faster, with no change in your source. Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like Java's, that emit machine code on the fly instead of interpreting your Python program step by step. The result is that your unmodified Python programs run faster. Benefits 2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module. Drawbacks Psyco currently uses quite a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.
2003-10-02 00:39:06 +02:00
${PYSITELIB}/psyco/logger.py
${PYSITELIB}/psyco/logger.pyc
${PYSITELIB}/psyco/logger.pyo
${PYSITELIB}/psyco/profiler.py
${PYSITELIB}/psyco/profiler.pyc
${PYSITELIB}/psyco/profiler.pyo
${PYSITELIB}/psyco/support.py
${PYSITELIB}/psyco/support.pyc
${PYSITELIB}/psyco/support.pyo
@dirrm ${PYSITELIB}/psyco
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