Mailman 3 November 2009 - Cplusplus-sig

boost::python embedding error - runtime - Mac OS X - 1.38
by Igor Karpov Oct. 1, 2014

Oct. 1, 2014

Hi, I am trying to run the following program: #include <iostream> #include <Python.h> #include <boost/python.hpp> using namespace boost::python; using namespace std; int main(int argc, char** argv) { { // Using Python/C Py_Initialize(); PyObject* main_module = PyImport_ImportModule("__main__"); PyObject* globals = PyEval_GetGlobals(); PyObject* locals = PyEval_GetLocals(); PyRun_SimpleString("print 'Hello World, from Python/C!'\n"); Py_Finalize(); } { // Using boost::python Py_Initialize(); object main_module = import("__main__"); object main_namespace = main_module.attr("__dict__"); try { object ignored = exec("print 'Hello World, from boost::python!'\n", main_namespace); Py_Finalize(); } catch (error_already_set const& e) { PyErr_Print(); return 1; } } return 0; } on Linux (both x86 and x86_64), with Ubuntu's default version of Boost (1.34.1) installed, I am able to do so as expected: $ ./embed Hello World, from Python/C! Hello World, from boost::python! on Mac OS X, I get a runtime error: $ ./embed Hello World, from Python/C! Bus Error Running with gdb, this is the stack trace: Hello World, from Python/C! Program received signal EXC_BAD_ACCESS, Could not access memory. Reason: KERN_PROTECTION_FAILURE at address: 0x00000000 0x00000000 in ?? () (gdb) where #0 0x00000000 in ?? () #1 0x00bb618f in PyEval_GetGlobals () #2 0x00bce0dd in PyImport_Import () #3 0x00bce2b0 in PyImport_ImportModule () #4 0x008127d4 in boost::python::import (name=@0xbffff4a8) at libs/python/src/import.cpp:20 #5 0x00004446 in main (argc=1, argv=0xbffff510) at embed.cc:22 For this Mac, boost version is latest (1.38) and python version is: Python 2.5.4 (r254:67917, Dec 23 2008, 14:57:27) [GCC 4.0.1 (Apple Computer, Inc. build 5363)] on darwin Is this a bug? I attached the source and the cmake file I am using to build, for convenience. Thanks, --Igor.

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CMake and getting starting with boost.python
by Braddock Gaskill Aug. 5, 2011

Aug. 5, 2011

Yesterday I became a boost.python user, after years of heavy SWIG usage. I would have started using boost.python years ago except for the bjam learning curve. I spent hours TRYING on multiple occasions, but got lost every time trying to get the page one example to build with bjam. Here is how to build the "greet" example with a four line CMake file: cat >>CMakeLists.txt <<EOF LINK_LIBRARIES(boost_python) INCLUDE_DIRECTORIES("/usr/include/python2.5") LINK_DIRECTORIES("/usr/lib/python2.5") # Not needed? ADD_LIBRARY(hello SHARED hello.cpp) EOF You WILL have to `mv libhello.so hello.so` after building. Works for me under Ubuntu Linux 6.10 after apt-get install cmake python2.5-dev boost-python-dev cmake make mv libhello.so hello.so ipython In [1]: import hello In [2]: hello.greet() Out[2]: 'hello, world' Boost.Python has been a joy to learn and use since I got past bjam. I had a moderately large API wrapped in just my first couple hours of learning (less time than I spent messing with bjam). Any additional advice for using CMake to build boost.python? Braddock Gaskill

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How to import a boost::python dll in windows?
by ichijoji Aug. 5, 2011

Aug. 5, 2011

I'm trying to port some research code that uses boost::python to expose a library to python to windows, but I'm having trouble importing the dll into python. I'm compiling using msvc 2005 and using python 2.5, but when I try to import the module I get this: Traceback (most recent call last): File "main.py", line 1, in <module> import object File "c:\code\sge\code\scripts\object.py", line 1, in <module> import sge ImportError: No module named sge My module is named sge and I'm compiling to sge.dll. Is there some obvious reason why python wouldn't be able to find my dll? When I compile on linux into an so this code works fine. -- View this message in context: http://www.nabble.com/How-to-import-a-boost%3A%3Apython-dll-in-windows--tf3… Sent from the Python - c++-sig mailing list archive at Nabble.com.

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Getting object for PyObject (reference counting)
by Murray Cumming Feb. 11, 2010

Feb. 11, 2010

I can't find any definitive documentation that tells me how I should get a boost::python::object to wrap an existing PyObject*. I guess that there's a way to do it that uses an existing reference, and a way that takes an extra reference. -- murrayc(a)murrayc.com www.murrayc.com www.openismus.com

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Re: [C++-sig] [python] python + phoenix
by lists_ravi＠lavabit.com Jan. 6, 2010

Jan. 6, 2010

>> I have some code that takes member function pointers of the form >> R Obj::*( A1, A2, A3, ..., An ) >> and converts them to a function object Q with the following signature: >> Rnew Q( Obj&, B1, B2, ..., Bn ) >> where >> Rnew = result_conversion_metafunction<R>::type >> Bi = arg_conversion_metafunction<Ai>::type >> and Q is exposed via boost.python as a member of Obj. >> >> For example, Ai could be a fixed-point number, with Bi being a double so >> that >> the python side does not know anything about fixed-point numbers. > > I gather that custom converters aren't preferred because: > > 1. It is a hassle to talk directly to the underlying raw PyObject > pointers and manage storage in the converter methods > > 2. The converted type still leaks out to python in docstrings > > Are there others? Or am I completely off? Neither of the above is a big issue. In fact, python-side knowledge of the converted type would even be mildly useful. The main problem is the number of types: my_fixed_point_type< int bit_width, // 1 to 63 int binary_pt_location, // -63 to 63 bool signed, property_tag // policies for rounding, etc. > std::complex< my_fixed_point_type<...> > boost::numeric::ublas::array< ... > boost::numeric::ublas::matrix< ... > There are simply far too many types to create converters for and to register explicitly. Therefore, I use inline functions/functors to do all the conversions on the C++ side, and python knows only about real and complex doubles. > > An instance >> of Q would convert eh floating point numbers passed from the python side >> into >> fixed-point numbers, call the member function, and convert the returned >> value >> to a double for use on the python side. >> >> For these "converters", metafunctions from boost.function_types are used >> to >> obtain the mpl::vector specifying result type and argument types. >> Extending >> the technique above to function objects which take Obj* as their first >> argument, I have a protocol which relies on the presence of a typedef >> called >> 'components' in the function object so that I can use the converter when >> exposing via boost.python: >> >> struct my_functor { >> typedef mpl::vector<R, Obj*, A1, A2, A3, A4> components; >> R operator()( Obj*, A1, A2, A3, A4 ) { ... } >> }; > > To be sure I'm following you, correct me: > > * for each member function signature that you wrap, you have a matching > my_functor that calls it > * my_functor does nothing but call the member function it wraps > * my_converter<my_functor>::type does the conversion from Rnew (B1, B2, > ... Bn) to R (A1, A2, ...An) and calls my_functor. > > Have I got it? Yes. > It is all very interesting, and to a certain degree duplicates some > functionality in detail/caller.hpp. How do you generate these > my_functors... preprocessor? fusion? Mostly boost.preprocessor (with some template metaprogramming using mpl). Fusion doesn't work very well for me since the effort needed to get my functors into a form usable from fusion is greater than just coding my own invocation functions via boost.preprocessor; pseudo-code: template <typename Func> struct my_converter { Func f_; typedef typename ft::components<F>::type components; typedef typename arg_converter<components>::type arg_types; typedef typename result_converter<components>::type result_type; // Shown for non-void return with one argument; can be generalized // using enable_if for void types and using boost.preprocessor for // different numbers of arguments result_type operator()( typename at_c<1,arg_types>::type a1 ) { return convert_result<result_type>( f_( convert_arg<typename at_c<1,components>::type>( a1 ) ) ); } }; template <typename Func> my_converter<Func> make_converted_func( Func f ) { return my_converter<Func>( f ); } > I'm wondering if there isn't motivation here to cleanly integrate a > general facility for additional c++-side type conversions. The > following came to mind, which imitates a function type style that > boost::proto uses extensively: > > struct hidden_type; // python shouldn't see this at all > > struct int_2_hidden // converts python-side 'int' to hidden > { > typedef hidden_type result_type; > > hidden_type operator()(int) const; > }; > > // fnobj takes a hidden, doesn't know it is wrapped in python > struct fnobj { > typedef void result_type; > void operator()(float, hidden_type); > }; > > def("myfunctor", as<void(float, int_to_hidden(int))>(fnobj())); > > where int_to_hidden(int) is a function type (not a function call, but it > later becomes a function call), indicating that what python passes > should be converted to int, then the int converted to hidden_type via an > instance of int_to_hidden, then the hidden_type passed to the underlying > instance of fnobj. > > I realize this doesn't involve using the mpl::vectors you've already > calculated, just throwing it out there. Such a general facility would probably be better than my code and would be greatly useful for me, but are there enough people out there with this use case? I don't care about using mpl::vector if there is a more general solution. >> // my_converter uses the components typedef >> typedef typename my_converter<my_functor>::type Q; > > so Q could have a nested typedef (note I say Rnew, not R): > > typedef mpl::vector<Rnew, Obj*, B1, B2, B3, B4> components; > > or use that in combination with function_types to synthesize > > typedef Rnew(Obj*, B1, B2, B3, B4) signature; Yes. Regards, Ravi

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Embedding Python - creating Python objects from C++
by Sohail Somani Nov. 30, 2009

Nov. 30, 2009

I have a class in C++ as follows: class Base { virtual ~Base() /* ideally like = 0 but doesn't seem to work */; }; I export this class to Python: class_<Base>("Base",no_init); The user is expected to create a derived class: class UserClass(Base): ... stuff here ... What I want to do then (in C++) is create instances of this Python class that are stored using a shared pointer: // constructs a new instance of UserClass in Python using magic // but uses shared_ptr to keep alive shared_ptr<Base> base(/* magic here */); I understand that I can do something like module.attr("UserClass")() to create an instance but that will return an object instance which doesn't seem like it would play nice if I extracted a Base pointer from it. So does anyone know how to implement the above referenced magic? It sounds like it should be obvious, but I'm not sure. Thanks, and sorry if this is a newb question! Sohail

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Getting Boost.Python Working on MacOS X
by Martin Hediger Nov. 25, 2009

Nov. 25, 2009

Dear All I have been trying to get Boost.Python working on my MBP with Mac OS 10.5, since I need it to compile the chemical modeling software "AVOGADRO" for modification reasons. I pretty much followed the instructions on both the Boost, Getting Started guide and the Boost.Python Introduction. I managed to get the "Lambda" and the "Regex" examples working perfectly, but unfortunatly not the python "embedding" and "extending" examples, neither as well the "hello world". Apparently, no embedding/extending module is being built for me to import in the python-test script following the build. My setup is as follows: Boost root: /usr/local/boost_1_40_0/ (so I call every command with sudo). The lambda and regex example files (.cpp) were perfectly compiling in a directory ~/programming_tests/, so my compiler is very likely to work. In order to do so, I issued the command: cpp+ -I example.cpp -o example /usr/local/boost_1_40_0/lib/libboost_regex-mt.a for some (possibly to the overall problem related) reason, it does not work with the dynamic library .dylib. What would be the basic procedure to get the boost.python examples running on Mac OS X? Thanks a lot for any suggestions.

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boost python and weak_ptr from a shared_ptr argument
by Jahn Fuchs Nov. 25, 2009

Nov. 25, 2009

Hello boost python users, I really like boost python but I stumbled in a problem I don't know how to solve, maybe you have an idea: I have a class KnowledgeBase that holds an shared_ptr to an KBObject and also a weak_ptr to an KBObject. If I set the shared_ptr with the set_shared_ptr function it works fine, but it doesn't work with the set_weak_ptr function (which takes a shared_ptr as an argument) ... see the following C++ code, python export code and python test code to see what i mean. I made a simple example which I also tested and it shows the problem I have. Thank you in advance. jahn. // C++ CODE: ------------------------------------------------------------------------- class KBObject { public: std::string name; }; class KnowledgeBase { public: boost::shared_ptr<KBObject> obj_shared_ptr; boost::weak_ptr<KBObject> obj_weak_ptr; void set_weak_ptr(boost::shared_ptr<KBObject> obj_ptr) { obj_weak_ptr = boost::weak_ptr<KBObject>(obj_ptr); }; void set_shared_ptr(boost::shared_ptr<KBObject> obj_ptr) { obj_shared_ptr = obj_ptr; }; boost::shared_ptr<KBObject> get_shared_ptr() { return obj_shared_ptr; }; boost::shared_ptr<KBObject> get_weak_ptr() { return obj_weak_ptr.lock(); }; void print_weak_ptr() { if (boost::shared_ptr<KBObject> obj_ptr = obj_weak_ptr.lock()) std::cout << obj_ptr.get()->name << std::endl; else std::cout << "NO OBJECT" << std::endl; }; void print_shared_ptr() { if (obj_shared_ptr.get()!=0) std::cout << obj_shared_ptr.get()->name << std::endl; else std::cout << "NO OBJECT" << std::endl; }; }; // PYTHON MODULE EXPORT ---------------------------------------------- BOOST_PYTHON_MODULE(kbpython) { using namespace boost::python; class_<KBObject, boost::shared_ptr<KBObject> >("KBObject") .def_readwrite("name", &KBObject::name) ; class_<KnowledgeBase>("KnowledgeBase") .def("set_shared_ptr", &KnowledgeBase::set_shared_ptr) .def("set_weak_ptr", &KnowledgeBase::set_weak_ptr) .def("get_shared_ptr", &KnowledgeBase::get_shared_ptr) .def("get_weak_ptr", &KnowledgeBase::get_weak_ptr) .def("print_weak_ptr", &KnowledgeBase::print_weak_ptr) .def("print_shared_ptr", &KnowledgeBase::print_shared_ptr) ; } // PYTHON TEST PROGRAM ----------------------------------------------- #!/usr/bin/env python import kbpython kb = kbpython.KnowledgeBase() obj = kbpython.KBObject() obj.name = "myObject" kb.set_shared_ptr(obj) kb.print_shared_ptr() obj_2 = kb.get_shared_ptr() obj_2.name = "change_name" kb.print_shared_ptr() kb.set_weak_ptr(obj_2) kb.print_weak_ptr() ------------------------------------------------------------------------

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building modules with MSVC
by Simon Pickles Nov. 25, 2009

Nov. 25, 2009

Hi, Is it possible to build boost::python modules using MSVC as opposed to bjam? I'd like MSVC to output a pyd of course. Thanks Simon

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multithreading and interpreters
by Trigve Siver Nov. 24, 2009

Nov. 24, 2009

Hi, I'm working on project where we used boost.python (embedded). In general I have the "modules" where each module is something like sandbox, is isolated from others modules and run in solo thread. I want to be able to use python (and boost python functions of course) from each module thread. Something like that each thread could have own interpreter without need to take care of GIL and like. Is it possible? I know there could be some problems with GIL and so. I've found in python C API docs Py_NewInterpreter() function which could be of help (or not?). So will this configuration work? Could be there some problems with boost.python when using multiple threads? Thanks Trigve

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