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Boost.Python - FAQ
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<a href="../index.html">Boost.Python</a>
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Frequently Asked Questions (FAQs)
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<hr>
<dl class="page-index">
<dt>
<a href="#question1">Is return_internal_reference efficient?</a>
</dt>
<dt>
<a href="#question2">How can I wrap functions which take C++
containers as arguments?</a>
</dt>
<dt>
<a href="#c1204">fatal error C1204:Compiler limit:internal structure
overflow</a>
</dt>
<dt>
<a href="#debugging">How do I debug my Python extensions?</a>
</dt>
<dt>
<a href="#imul">Why doesn't my <code>*=</code> operator work?</a>
</dt>
<dt>
<a href="#macosx">Does Boost.Python work with Mac OS X?</a>
</dt>
<dt>
<a href="#xref">How can I find the existing PyObject that holds a C++
object?</a>
</dt>
<dt>
<a href="#ownership">How can I wrap a function which needs to take
ownership of a raw pointer?</a>
</dt>
</dl>
<hr>
<h2>
<a name="question1"></a>Is return_internal_reference efficient?
</h2>
<blockquote>
<b>Q:</b> <i>I have an object composed of 12 doubles. A const&amp; to
this object is returned by a member function of another class. From the
viewpoint of using the returned object in Python I do not care if I get
a copy or a reference to the returned object. In Boost.Python Version 2
I have the choice of using copy_const_reference or
return_internal_reference. Are there considerations that would lead me
to prefer one over the other, such as size of generated code or memory
overhead?</i>
<p>
<b>A:</b> copy_const_reference will make an instance with storage for
one of your objects, size = base_size + 12 * sizeof(double).
return_internal_reference will make an instance with storage for a
pointer to one of your objects, size = base_size + sizeof(void*).
However, it will also create a weak reference object which goes in
the source object's weakreflist and a special callback object to
manage the lifetime of the internally-referenced object. My guess?
copy_const_reference is your friend here, resulting in less overall
memory use and less fragmentation, also probably fewer total cycles.
</p>
</blockquote>
<hr>
<h2>
<a name="question2"></a>How can I wrap functions which take C++
containers as arguments?
</h2>
<p>
Ralf W. Grosse-Kunstleve provides these notes:
</p>
<ol>
<li>
Using the regular <code>class_&lt;&gt;</code> wrapper:
<pre>
class_&lt;std::vector&lt;double&gt; &gt;("std_vector_double")
.def(...)
...
;
</pre>This can be moved to a template so that several types (double, int,
long, etc.) can be wrapped with the same code. This technique is used in the
file
<blockquote>
scitbx/include/scitbx/array_family/boost_python/flex_wrapper.h
</blockquote>in the "scitbx" package. The file could easily be
modified for wrapping std::vector&lt;&gt; instantiations.
<p>
This type of C++/Python binding is most suitable for containers
that may contain a large number of elements (&gt;10000).
</p>
</li>
<li>
Using custom rvalue converters. Boost.Python "rvalue converters"
match function signatures such as:
<pre>
void foo(std::vector&lt;double&gt; const&amp; array); // pass by const-reference
void foo(std::vector&lt;double&gt; array); // pass by value
</pre>Some custom rvalue converters are implemented in the file
<blockquote>
scitbx/include/scitbx/boost_python/container_conversions.h
</blockquote>This code can be used to convert from C++ container
types such as std::vector&lt;&gt; or std::list&lt;&gt; to Python
tuples and vice versa. A few simple examples can be found in the file
<blockquote>
scitbx/array_family/boost_python/regression_test_module.cpp
</blockquote>Automatic C++ container &lt;-&gt; Python tuple
conversions are most suitable for containers of moderate size. These
converters generate significantly less object code compared to
alternative 1 above.
</li>
</ol>A disadvantage of using alternative 2 is that operators such as
arithmetic +,-,*,/,% are not available. It would be useful to have custom
rvalue converters that convert to a "math_array" type instead of tuples.
This is currently not implemented but is possible within the framework of
Boost.Python V2 as it will be released in the next couple of weeks. [ed.:
this was posted on 2002/03/10]
<p>
It would also be useful to also have "custom lvalue converters" such as
std::vector&lt;&gt; &lt;-&gt; Python list. These converters would
support the modification of the Python list from C++. For example:
</p>
<p>
C++:
</p>
<pre>
void foo(std::vector&lt;double&gt;&amp; array)
{
for(std::size_t i=0;i&lt;array.size();i++) {
array[i] *= 2;
}
}
</pre>Python:
<pre>
&gt;&gt;&gt; l = [1, 2, 3]
&gt;&gt;&gt; foo(l)
&gt;&gt;&gt; print l
[2, 4, 6]
</pre>Custom lvalue converters require changes to the Boost.Python core
library and are currently not available.
<p>
P.S.:
</p>
<p>
The "scitbx" files referenced above are available via anonymous CVS:
</p>
<pre>
cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx login
cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx co scitbx
</pre>
<hr>
<h2>
<a name="c1204"></a>fatal error C1204:Compiler limit:internal structure
overflow
</h2>
<blockquote>
<b>Q:</b> <i>I get this error message when compiling a large source
file. What can I do?</i>
<p>
<b>A:</b> You have two choices:
</p>
<ol>
<li>
Upgrade your compiler (preferred)
</li>
<li>
Break your source file up into multiple translation units.
<p>
<code><b>my_module.cpp</b></code>:
</p>
<pre>
...
void more_of_my_module();
BOOST_PYTHON_MODULE(my_module)
{
def("foo", foo);
def("bar", bar);
...
more_of_my_module();
}
</pre><code><b>more_of_my_module.cpp</b></code>:
<pre>
void more_of_my_module()
{
def("baz", baz);
...
}
</pre>If you find that a <code><a href=
"class.html#class_-spec">class_</a>&lt;...&gt;</code> declaration can't fit
in a single source file without triggering the error, you can always pass a
reference to the <code>class_</code> object to a function in another source
file, and call some of its member functions (e.g. <code>.def(...)</code>) in
the auxilliary source file:
<p>
<code><b>more_of_my_class.cpp</b></code>:
</p>
<pre>
void more_of_my_class(class&lt;my_class&gt;&amp; x)
{
x
.def("baz", baz)
.add_property("xx", &amp;my_class::get_xx, &amp;my_class::set_xx)
;
...
}
</pre>
</li>
</ol>
</blockquote>
<hr>
<h2>
<a name="debugging"></a>How do I debug my Python extensions?
</h2>
<p>
Greg Burley gives the following answer for Unix GCC users:
</p>
<blockquote>
Once you have created a boost python extension for your c++ library or
class, you may need to debug the code. Afterall this is one of the
reasons for wrapping the library in python. An expected side-effect or
benefit of using BPL is that debugging should be isolated to the c++
library that is under test, given that python code is minimal and
boost::python either works or it doesn't. (ie. While errors can occur
when the wrapping method is invalid, most errors are caught by the
compiler ;-).
<p>
The basic steps required to initiate a gdb session to debug a c++
library via python are shown here. Note, however that you should
start the gdb session in the directory that contains your BPL
my_ext.so module.
</p>
<pre>
(gdb) target exec python
(gdb) run
&gt;&gt;&gt; from my_ext import *
&gt;&gt;&gt; [C-c]
(gdb) break MyClass::MyBuggyFunction
(gdb) cont
&gt;&gt;&gt; pyobj = MyClass()
&gt;&gt;&gt; pyobj.MyBuggyFunction()
Breakpoint 1, MyClass::MyBuggyFunction ...
Current language: auto; currently c++
(gdb) do debugging stuff
</pre>
</blockquote>
<p>
Greg's approach works even better using Emacs' "<code>gdb</code>"
command, since it will show you each line of source as you step through
it.
</p>
<p>
On <b>Windows</b>, my favorite debugging solution is the debugger that
comes with Microsoft Visual C++ 7. This debugger seems to work with
code generated by all versions of Microsoft and Metrowerks toolsets;
it's rock solid and "just works" without requiring any special tricks
from the user.
</p>
<p>
Unfortunately for Cygwin and MinGW users, as of this writing gdb on
Windows has a very hard time dealing with shared libraries, which could
make Greg's approach next to useless for you. My best advice for you is
to use Metrowerks C++ for compiler conformance and Microsoft Visual
Studio as a debugger when you need one.
</p>
<h3>
Debugging extensions through Boost.Build
</h3>If you are launching your extension module tests with <a href=
"../../../tools/build">Boost.Build</a> using the
<code>boost-python-runtest</code> rule, you can ask it to launch your
debugger for you by adding "-sPYTHON_LAUNCH=<i>debugger</i>" to your bjam
command-line:
<pre>
bjam -sTOOLS=metrowerks "-sPYTHON_LAUNCH=devenv /debugexe" test
bjam -sTOOLS=gcc -sPYTHON_LAUNCH=gdb test
</pre>It can also be extremely useful to add the <code>-d+2</code> option
when you run your test, because Boost.Build will then show you the exact
commands it uses to invoke it. This will invariably involve setting up
PYTHONPATH and other important environment variables such as LD_LIBRARY_PATH
which may be needed by your debugger in order to get things to work right.
<hr>
<h2>
<a name="imul"></a>Why doesn't my <code>*=</code> operator work?
</h2>
<blockquote>
<b>Q:</b> <i>I have exported my class to python, with many overloaded
operators. it works fine for me except the</i> <code>*=</code>
<i>operator. It always tells me "can't multiply sequence with non int
type". If I use</i> <code>p1.__imul__(p2)</code> <i>instead of</i>
<code>p1 *= p2</code><i>, it successfully executes my code. What's
wrong with me?</i>
<p>
<b>A:</b> There's nothing wrong with you. This is a bug in Python
2.2. You can see the same effect in Pure Python (you can learn a lot
about what's happening in Boost.Python by playing with new-style
classes in Pure Python).
</p>
<pre>
&gt;&gt;&gt; class X(object):
... def __imul__(self, x):
... print 'imul'
...
&gt;&gt;&gt; x = X()
&gt;&gt;&gt; x *= 1
</pre>To cure this problem, all you need to do is upgrade your Python to
version 2.2.1 or later.
</blockquote>
<hr>
<h2>
<a name="macosx"></a>Does Boost.Python work with Mac OS X?
</h2>
<blockquote>
<p>
The short answer: as of January 2003, unfortunately not.
</p>
<p>
The longer answer: using Mac OS 10.2.3 with the December Developer's
Kit, Python 2.3a1, and bjam's darwin-tools.jam, Boost.Python compiles
fine, including the examples. However, there are problems at runtime
(see <a href=
"http://mail.python.org/pipermail/c++-sig/2003-January/003267.html">http://mail.python.org/pipermail/c++-sig/2003-January/003267.html</a>).
Solutions are currently unknown.
</p>
<p>
It is known that under certain circumstances objects are
double-destructed. See <a href=
"http://mail.python.org/pipermail/c++-sig/2003-January/003278.html">http://mail.python.org/pipermail/c++-sig/2003-January/003278.html</a>
for details. It is not clear however if this problem is related to
the Boost.Python runtime issues.
</p>
</blockquote>
<hr>
<h2>
<a name="xref">How can I find the existing PyObject that holds a C++
object?</a>
</h2>
<blockquote>
"I am wrapping a function that always returns a pointer to an
already-held C++ object."
</blockquote>One way to do that is to hijack the mechanisms used for
wrapping a class with virtual functions. If you make a wrapper class with
an initial PyObject* constructor argument and store that PyObject* as
"self", you can get back to it by casting down to that wrapper type in a
thin wrapper function. For example:
<pre>
class X { X(int); virtual ~X(); ... };
X* f(); // known to return Xs that are managed by Python objects
// wrapping code
struct X_wrap : X
{
X_wrap(PyObject* self, int v) : self(self), X(v) {}
PyObject* self;
};
handle&lt;&gt; f_wrap()
{
X_wrap* xw = dynamic_cast&lt;X_wrap*&gt;(f());
assert(xw != 0);
return handle&lt;&gt;(borrowed(xw-&gt;self));
}
...
def("f", f_wrap());
class_&lt;X,X_wrap&gt;("X", init&lt;int&gt;())
...
;
</pre>Of course, if X has no virtual functions you'll have to use
<code>static_cast</code> instead of <code>dynamic_cast</code> with no runtime
check that it's valid. This approach also only works if the <code>X</code>
object was constructed from Python, because <code>X</code>s constructed from
C++ are of course never <code>X_wrap</code> objects.
<p>
Another approach to this requires some work on Boost.Python, but it's
work we've been meaning to get to anyway. Currently, when a
<code>shared_ptr&lt;X&gt;</code> is converted from Python, the
shared_ptr actually manages a reference to the containing Python
object. I plan to make it so that when a shared_ptr&lt;X&gt; is
converted back to Python, the library checks to see if it's one of
those "Python object managers" and if so just returns the original
Python object. To exploit this you'd have to be able to change the C++
code you're wrapping so that it deals with shared_ptr instead of raw
pointers.
</p>
<p>
There are other approaches too. The functions that receive the Python
object that you eventually want to return could be wrapped with a thin
wrapper that records the correspondence between the object address and
its containing Python object, and you could have your f_wrap function
look in that mapping to get the Python object out.
</p>
<h2>
<a name="ownership">How can I wrap a function which needs to take
ownership of a raw pointer?</a>
</h2>
<blockquote>
<i>Part of an API that I'm wrapping goes something like this:</i>
<pre>
struct A {}; struct B { void add( A* ); }
where B::add() takes ownership of the pointer passed to it.
</pre>
<p>
<i>However:</i>
</p>
<pre>
a = mod.A()
b = mod.B()
b.add( a )
del a
del b
# python interpreter crashes
# later due to memory corruption.
</pre>
<p>
<i>Even binding the lifetime of a</i> to b via
with_custodian_and_ward doesn't prevent the python object a from
ultimately trying to delete the object it's pointing to. Is there a
way to accomplish a 'transfer-of-ownership' of a wrapped C++ object?
</p>
<p>
<i>--Bruce Lowery</i>
</p>
</blockquote>Yes: Make sure the C++ object is held by auto_ptr:
<pre>
class_&lt;A, std::auto_ptr&lt;A&gt; &gt;("A")
...
;
</pre>Then make a thin wrapper function which takes an auto_ptr parameter:
<pre>
void b_insert(B&amp; b, std::auto_ptr&lt;A&gt; a)
{
b.insert(a.get());
a.release();
}
</pre>Wrap that as B.add. Note that pointers returned via
<code><a href="manage_new_object.html#manage_new_object-spec">manage_new_object</a></code>
will also be held by <code>auto_ptr</code>, so this
transfer-of-ownership will also work correctly.
<hr>
<p>
Revised
<!--webbot bot="Timestamp" S-Type="EDITED" S-Format="%d %B, %Y" startspan -->
23 January, 2003
<!--webbot bot="Timestamp" endspan i-checksum="39359" -->
</p>
<p>
<i>&copy; Copyright <a href="../../../../people/dave_abrahams.htm">Dave
Abrahams</a> 2002-2003. All Rights Reserved.</i>
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