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167 lines
5.9 KiB
HTML
167 lines
5.9 KiB
HTML
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
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<html>
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<head>
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<meta name="generator" content=
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"HTML Tidy for Windows (vers 1st August 2002), see www.w3.org">
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<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
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<link rel="stylesheet" type="text/css" href="../boost.css">
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<title>Boost.Python - FAQ</title>
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</head>
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<body link="#0000ff" vlink="#800080">
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<table border="0" cellpadding="7" cellspacing="0" width="100%" summary=
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"header">
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<tr>
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<td valign="top" width="300">
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<h3><a href="../../../../index.htm"><img height="86" width="277"
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alt="C++ Boost" src="../../../../c++boost.gif" border="0"></a></h3>
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</td>
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<td valign="top">
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<h1 align="center">Boost.Python</h1>
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<h2 align="center">Frequently Asked Questions (FAQs)</h2>
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</td>
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</tr>
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</table>
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<hr>
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<dl class="page-index">
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<dt><a href="#question1">Is return_internal reference
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efficient?</a></dt>
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<dt><a href="#question2">How can I wrap containers which take C++
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containers as arguments?</a></dt>
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</dl>
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<h2><a name="question1"></a>Is return_internal reference efficient?</h2>
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<blockquote>
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<b>Q:</b> <i>I have an object composed of 12 doubles. A const& to
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this object is returned by a member function of another class. From the
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viewpoint of using the returned object in Python I do not care if I get
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a copy or a reference to the returned object. In Boost.Python Version 2
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I have the choice of using copy_const_reference or
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return_internal_reference. Are there considerations that would lead me
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to prefer one over the other, such as size of generated code or memory
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overhead?</i>
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<p><b>A:</b> copy_const_reference will make an instance with storage
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for one of your objects, size = base_size + 12 * sizeof(double).
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return_internal_reference will make an instance with storage for a
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pointer to one of your objects, size = base_size + sizeof(void*).
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However, it will also create a weak reference object which goes in the
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source object's weakreflist and a special callback object to manage the
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lifetime of the internally-referenced object. My guess?
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copy_const_reference is your friend here, resulting in less overall
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memory use and less fragmentation, also probably fewer total
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cycles.</p>
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</blockquote>
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<h2><a name="question2"></a>How can I wrap functions which take C++
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containers as arguments?</h2>
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<p>Ralf W. Grosse-Kunstleve provides these notes:</p>
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<ol>
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<li>
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Using the regular <code>class_<></code> wrapper:
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<pre>
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class_<std::vector<double> >("std_vector_double")
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.def(...)
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...
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;
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</pre>
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This can be moved to a template so that several types (double, int,
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long, etc.) can be wrapped with the same code. This technique is used
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in the file
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<blockquote>
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scitbx/include/scitbx/array_family/boost_python/flex_wrapper.h
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</blockquote>
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in the "scitbx" package. The file could easily be modified for
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wrapping std::vector<> instantiations.
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<p>This type of C++/Python binding is most suitable for containers
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that may contain a large number of elements (>10000).</p>
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</li>
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<li>
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Using custom rvalue converters. Boost.Python "rvalue converters"
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match function signatures such as:
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<pre>
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void foo(std::vector<double> const& array); // pass by const-reference
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void foo(std::vector<double> array); // pass by value
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</pre>
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Some custom rvalue converters are implemented in the file
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<blockquote>
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scitbx/include/scitbx/boost_python/container_conversions.h
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</blockquote>
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This code can be used to convert from C++ container types such as
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std::vector<> or std::list<> to Python tuples and vice
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versa. A few simple examples can be found in the file
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<blockquote>
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scitbx/array_family/boost_python/regression_test_module.cpp
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</blockquote>
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Automatic C++ container <-> Python tuple conversions are most
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suitable for containers of moderate size. These converters generate
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significantly less object code compared to alternative 1 above.
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</li>
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</ol>
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A disadvantage of using alternative 2 is that operators such as
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arithmetic +,-,*,/,% are not available. It would be useful to have custom
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rvalue converters that convert to a "math_array" type instead of tuples.
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This is currently not implemented but is possible within the framework of
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Boost.Python V2 as it will be released in the next couple of weeks. [ed.:
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this was posted on 2002/03/10]
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<p>It would also be useful to also have "custom lvalue converters" such
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as std::vector<> <-> Python list. These converters would
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support the modification of the Python list from C++. For example:</p>
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<p>C++:</p>
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<pre>
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void foo(std::vector<double>& array)
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{
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for(std::size_t i=0;i<array.size();i++) {
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array[i] *= 2;
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}
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}
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</pre>
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Python:
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<pre>
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>>> l = [1, 2, 3]
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>>> foo(l)
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>>> print l
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[2, 4, 6]
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</pre>
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Custom lvalue converters require changes to the Boost.Python core library
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and are currently not available.
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<p>P.S.:</p>
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<p>The "scitbx" files referenced above are available via anonymous
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CVS:</p>
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<pre>
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cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx login
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cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx co scitbx
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</pre>
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<hr>
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<p>Revised
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<!--webbot bot="Timestamp" S-Type="EDITED" S-Format="%d %B, %Y" startspan -->
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05 November, 2002
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<!--webbot bot="Timestamp" endspan i-checksum="39359" -->
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</p>
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<p><i>© Copyright <a href=
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"../../../../people/dave_abrahams.htm">Dave Abrahams</a> 2002. All Rights
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Reserved.</i></p>
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</body>
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</html>
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