Mailman 3 January 2004 - Cplusplus-sig

RE: [C++-sig] Re: Wrapper for exception translation
by Gottfried.Ganssauge＠HAUFE.DE Dec. 13, 2004

Dec. 13, 2004

> > ... > >> > >> > Currently, in order to wrap user defined exceptions you need to > >> > > >> > - allocate a python exception using PyErr_NewException > >> > >> Well, no. I don't see any call to PyErr_NewException in > >> libs/python/test/exception_translator.cpp > > > > Right, you don't need to if you are content with RuntimeError > > exceptions. > > or any other pre-packaged exception type provided by Python. > > > My objective was another one: I wanted to create module exceptions > > that are derived from the python "Exception" class. > >> > >> > This function needs to be parametrized using a specific naming > >> > convention > >> > >> It's not clear to me what you're referring to. Are you > sure you mean > >> "naming convention"? > > Yes. > > From the documentation to PyErr_NewException: > > > > ... The __module__ attribute of the new class is set to > the first part > > (up to the last dot) of the name argument, and the > class name is set to > > the last part (after the last dot). > > ...yeah, that's a naming convention, but I don't see how that affects > the parameterization of any function. It is enforced by PyErr_NewException, so you must follow this convention. On the hand I don't think that any user of boost.python is aware of that convention, so I wanted to codify it within my facility. ... > > What I wanted to achieve was the following: > > Create an instance of a translated_exception_handler<> t > which will be > > registered with the library by calling > > register_exception_translator<>(). > > Sorry to be difficult, but I'm going to contradict you. You didn't > want any of that. What you wanted was to create a new Python > exception type in the module which would correspond to a particular > C++ exception type and would be raised at the boundary with Python > whenever a wrapped function threw the C++ exception. Right? Right. I actually described the way to do it within the current library design. > > > Normally t would be destructed by the end of exception_<>() thereby > > leaving a registration to a non-existing translator - very bad > > karma. > > I don't understand any of this. All you have to pass to > register_exception_translator is a function pointer, and functions > live forever. So where's the lifetime issue? A pointer to a function which has access to python exception instance e. As I didn't want to create separate entities I chose to supply a functor instead which has e as a member variable. > > > Because I didn't like to have an additional container for all > > translated_exception_handler<> instances, I chose to store t within > > e's class dictionary. At that moment it seemed to be the easiest > > way to create a wrapper class using class_<> instead of making a > > true python class by hand (and it even works!). You are right, it > > is way too complex, I will change it to the mechanism I used in > > opaque_pointer_converter. > > I don't know what that is, but before you consider doing something > which is again too complex, please consider: > > template <class E> > struct translate_exception > { > static char const* msg; This would need to be defined somewhere. > static object python_exception_type; ... and this would need to be defined somewhere as well. > > static void handler(E const&) > { > PyErr_SetString(python_exception_type.ptr(), msg.c_str()); > }; > > translate_exception(char const* python_exception_name, > char const* msg_) > { > // need fancier name manipulation here > python_exception_type > = object( > handle<>(PyErr_NewException(name))); > msg = msg_; > register_exception_translator<E>(handler); > } > }; > > > Simple. Yes. ... > > I'll make a redesign ... At times you don't see the forrest, just trees ... I think this time I have a simple facility which is also easy to use (no macros). It could be even simpler with a completely different design but frankly - I have no clue how to implement that: We would need a way to somehow derive (in the python sense) a class_<> from PyExc_Exception (the type of the python Exception class) or any other python class (PyErr_NewException() has a base parameter, which could be used for that). At the same time an exception_translator should be registered for that class_<> which uses PyErr_SetObject() to raise a copy of the exception caught. This would allow us to have true Python exceptions in a pythonic sense directly wrapped around the corresponding C++ exception. > > Thnx for your feedback. > > Cool! Looking forward to it. > > -- > Dave Abrahams > Boost Consulting > www.boost-consulting.com Cheers, Gottfried

3 7

Boost Python and Intel C++ 7.1 windows
by Xavier WARIN(Compte LOCAL) - I23 Aug. 16, 2004

Aug. 16, 2004

Hi, While compiling with Intel C++ 7.1 Boost Python , i get this kind of error on class.cpp and a lot of other Boost Python files : C:\boost-1.30.2\boost/type_traits/is_integral.hpp(39): error: class "boost::is_integral<unsigned short>" has already been defined BOOST_TT_AUX_BOOL_TRAIT_CV_SPEC1(is_integral,wchar_t,true) I think that there must be a define that i missed somewhere ! I don't find it Any idea ? Thank you Xavier Warin

2 2

wrapping interfaces and supplied implementations
by Brian Peters April 5, 2004

April 5, 2004

Hello All, I'd like first to thank the Boost.Python team and commend them on their creation. Dave Abrahams et.al. have implemented code the likes of which I could not even have conceived, let alone writen. Boost MPL is not something I could ever have thought up. My hope is simply that someone some day finds my work as useful and impressive as I find theirs. I am trying to wrap a library that implements a generic programming approach to computational geometry and topology. To achieve this it defines a number of interfaces it requires to do its job. For developers who do not wish to code the details of these interfaces it also supplies concrete implementations. Having observed Dave Abrahams' penchant for a working test case I have developed a sandbox representing a portion of the library. It has three classes that are abstract base classes: IFacade, IManager, and IProduct. All their pure virtual methods are defined using raw pointers to abstract base classes. The idea is that an application asks the facade for a manager [ IManager* IFacade::manager() ] and then uses the manager to create products [ IProduct* IManager::create(inti i) ]. The products have state that may be changed by the client or other operations of the facade. The manager can also store and retrieve products. A simple user can use the concrete Manager and Product classes supplied through these interfaces, but a more advanced user could derive their own product and manager from the abc's and pass that into the facade [ void IFacade::setManager(IManager* manager) ]. The old addage applies: "The simple should be easy, but the complex should be possible." i.e use the supplied system if you want, but you can always over ride it with something more complex. So now I want to be able to do the same thing in Python. I want to wrap everything so that a simple user can: * see the abstract base classes in python; i.e. the interfaces, their doc strings, etc. * use the supplied implementation of manager and product * derive their own products and manager if they want/need to in python Well, I got it all working! Not only working, but doing cool python stuff too. Being new to python I have found it interesting that arbitrary attributes and methods can be added to any object regardless of its class. I think of a wrapped Product passed out to python from the supplied Manager class as a python envelope containing the C++ Product. I can scribble on that envelope. Spill coffee on it. Crumple it up a bit. I can store it in the manager and throw it away. When I later retrieve from the manager, not only is it the same C++ Product (i.e same address), but it is the same PyObject (i.e. same address, or "id" as they call it in the interpreter), AND it even has the same note scribbled on it and the coffee stain! Its like decorating C++ classes dynamically at run time. I thought the article about C++/Python integration was cool when I read it a few months ago, but now I really see it. The line between Python and C++ is very fluid. ( http://www.cuj.com/documents/s=8188/cuj0307abrahams ) The code is attached below. For reference I am using the following (admittedly somewhat dated) environment: * Python 2.2.2 * Boost 1.30.0 * Windows NT4 with MSVC6 * RH linux 2.4.2-2 with g++ 1.96 I am offering this example to anyone that finds it useful. It is more complex than the examples I found in the documentation and code, yet still simple enough to examine in detail. I am hoping that those in the know will tell me if I have done anything terribly wrong. I will gladly explain why I have done things the way I have and/or share the verbose version of this sandbox that contains a lot more testing functions and cout's. This message is already too long to do so here. thanks, bfp ====================== > Brian Peters > topology<at>eircom<dot>net =============================================================================== ============ abcdf_ext.cpp ==================================================== #include <boost/python.hpp> #include <iostream> #include <sstream> using namespace boost::python; // --- component code ----------------------------------------------- // published interfaces struct IProduct { virtual ~IProduct() {} virtual int value() const = 0; virtual void set(int i) = 0; virtual int other(IProduct* product) const = 0; }; struct IManager { virtual ~IManager() {} virtual IProduct* create(int i) = 0; virtual IProduct* modify(IProduct* product) = 0; virtual int store(IProduct* product) = 0; virtual IProduct* retrieve(int index) = 0; }; struct IFacade { static IFacade* instance(); virtual ~IFacade() {} virtual IManager* manager() = 0; virtual void setManager(IManager* manager) = 0; virtual void update(int i) = 0; virtual std::string notice() const = 0; }; // supplied implementation of interfaces. // only exposed through pointers to the above interfaces. #define MANAGER_CAPACITY 10 struct Product : IProduct { Product(int i): _i(i) {} virtual ~Product() {} virtual int value() const { return _i; } virtual void set(int i) { _i = i; } virtual int other(IProduct* product) const { int v = -10; // TODO Should I throw if NULL == product??? if (product) v = product->value(); return _i*1000 + v; } int _i; }; struct Manager : IManager { Manager(): mCount(0) { memset(mProducts, 0, sizeof(mProducts)); } virtual ~Manager() {} virtual IProduct* create(int i) { return new Product(i); } virtual IProduct* modify(IProduct* product) { product->set(2 * product->value()); return product; } virtual int store(IProduct* product) { int index = -1; if (MANAGER_CAPACITY > mCount) { index = mCount; mProducts[mCount++] = product; } return index; } virtual IProduct* retrieve(int index) { IProduct* product = NULL; if (MANAGER_CAPACITY > index) product = mProducts[index]; return product; } int mCount; IProduct* mProducts[MANAGER_CAPACITY]; }; struct Facade : IFacade { Facade(): mManager(new Manager) {} virtual ~Facade() {} virtual IManager* manager() { return mManager; } virtual void setManager(IManager* manager) { // TODO Deleting the old manager will cause trouble if it has // already been sent out to python. How do I want to handle this? //if (mManager) // delete mManager; mManager = manager; } virtual void update(int delta) { // TODO get a product iterator from IManager here. IProduct* product; for (int i=0; i < MANAGER_CAPACITY; i++) { if (NULL != (product = mManager->retrieve(i))) product->set(product->value() + delta); } } virtual std::string notice() const { return "IFacade::notice() message: hello world!"; } IManager* mManager; }; // the singleton IFacade* theFacade = NULL; IFacade* IFacade::instance() { if (NULL == theFacade) theFacade = new Facade(); return theFacade; } // --- B.P.L. wrapper code ------------------------------------------- // rudimentary exception class struct error { error(std::string message): _msg(message) {} std::string const _msg; }; // ProductProxy provides abc methods to pass IProduct* to python. struct ProductProxy : IProduct { ProductProxy(IProduct* product) : mProduct(product) {} virtual ~ProductProxy() {} virtual int value() const { if (!mProduct) throw error("Bad proxy"); return mProduct->value(); } virtual void set(int i) { if (!mProduct) throw error("Bad proxy"); mProduct->set(i); } virtual int other(IProduct* product) const { if (!mProduct) throw error("Bad proxy"); return mProduct->other(product); } // this virtual function is overridden in ProductBase virtual int otherWrap(object& product) const { if (!mProduct) throw error("Bad proxy"); ProductProxy* proxy = arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); return mProduct->other(proxy); } IProduct* mProduct; }; // ProductBase is the heldtype for ProductProxy to let python derive from IProduct. struct ProductBase : ProductProxy { ProductBase(PyObject* pyobject): ProductProxy(NULL), mSelf(pyobject) {} virtual ~ProductBase() {} virtual int value() const { return call_method<int>(mSelf, "value"); } int default_value() const { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'value'"; throw error(msg.str()); } virtual void set(int i) { call_method<void>(mSelf, "set", i); } void default_set(int i) { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'set'"; throw error(msg.str()); } virtual int other(IProduct* product) const { ProductProxy proxy(product); return call_method<int>(mSelf, "other", ptr(&proxy)); } // this virtual function is overridden from ProductProxy virtual int otherWrap(object& product) const { return call_method<int>(mSelf, "other", product); } int default_other(object& product) const { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'other'"; throw error(msg.str()); } PyObject* mSelf; }; // ManagerProxy provides abc methods to pass IManager* to python. struct ManagerProxy : IManager { ManagerProxy(IManager* manager): mManager(manager), mCount(0) {} ManagerProxy(ManagerProxy& manager) : mManager(manager.mManager), mCount(manager.mCount) { for (int i=--mCount; 0 <= i; --i) mProducts[i] = manager.mProducts[i]; } virtual ~ManagerProxy() {} virtual IProduct* create(int i) { if (!mManager) throw error("Bad proxy"); return mManager->create(i); } // this virtual function is overridden in ManagerBase virtual object createWrap(int i) { if (NULL == mManager) throw error("Bad proxy"); return object(ptr(new ProductProxy(mManager->create(i)))); } virtual IProduct* modify(IProduct* product) { if (NULL == mManager) throw error("Bad proxy"); return mManager->modify(product); } // this virtual function is overridden in ManagerBase virtual object modifyWrap(object& product) { if (NULL == mManager) throw error("Bad proxy"); ProductProxy* proxy = arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); mManager->modify(proxy); return product; // IManager::modify returns its argument, but if another function might not, do this: //IProduct* value = mManager->anotherFunction(proxy); //return value == proxy ? product : object(ptr(new ProductProxy(value))); } virtual int store(IProduct* product) { return mManager->store(product); } virtual int storeWrap(object& product) { ProductProxy* proxy = arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); // make sure side effects will happen mManager->store(proxy->mProduct); int index = -1; if (MANAGER_CAPACITY > mCount) { index = mCount; mProducts[mCount++] = product; } return index; } virtual IProduct* retrieve(int index) { return mManager->retrieve(index); } virtual object retrieveWrap(int index) { // make sure side effects will happen mManager->retrieve(index); if (MANAGER_CAPACITY > index) return mProducts[index]; else return object(); // python's None } IManager* mManager; // just mirror the Manager approach to storage for sandbox int mCount; object mProducts[MANAGER_CAPACITY]; }; // ManagerBase is the heldtype for ManagerProxy to let python derive from IManager. struct ManagerBase : ManagerProxy { ManagerBase(PyObject* pyobject): ManagerProxy(NULL), mSelf(pyobject) {} virtual ~ManagerBase() {} virtual IProduct* create(int i) { object product = call_method<object>(mSelf, "create", i); return arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); } // this virtual function is overridden from ManagerProxy virtual object createWrap(int i) { return call_method<object>(mSelf, "create", i); } object default_create(int i) { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'create'"; throw error(msg.str()); } virtual IProduct* modify(IProduct* product) { ProductProxy proxy(product); return call_method<IProduct*>(mSelf, "modify", ptr(&proxy)); } // this virtual function is overridden from ManagerProxy virtual object modifyWrap(object& product) { return call_method<object>(mSelf, "modify", product); } object default_modify(object& product) { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'modify'"; throw error(msg.str()); } virtual int store(IProduct* product) { ProductProxy proxy(product); return call_method<int>(mSelf, "store", ptr(&proxy)); } virtual int storeWrap(object& product) { return call_method<int>(mSelf, "store", product); } int default_store(object& product) { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'store'"; throw error(msg.str()); } virtual IProduct* retrieve(int index) { object product = call_method<object>(mSelf, "retrieve", index); return arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); } virtual object retrieveWrap(int index) { return call_method<object>(mSelf, "retrieve", index); } object default_retrieve(int index) { std::ostringstream msg; msg << mSelf->ob_type->tp_name << " missing implementation of function 'retrieve'"; throw error(msg.str()); } PyObject* mSelf; }; // after IFacade, but no need to inherit struct FacadeProxy { ~FacadeProxy() {} static FacadeProxy* instance() { return new FacadeProxy(); } object managerWrap() { if (mManager == object()) mManager = object(ptr(new ManagerProxy(IFacade::instance()->manager()))); return mManager; } void setManagerWrap(object manager) { ManagerProxy* proxy = arg_from_python<ManagerProxy*>(manager.ptr())(manager.ptr()); if (NULL != proxy) { mManager = manager; IFacade::instance()->setManager(proxy); } else { std::ostringstream msg; msg << "Object type: " << manager.ptr()->ob_type->tp_name << " not derived from IManager"; throw error(msg.str()); } } void update(int delta) { IFacade::instance()->update(delta); } std::string notice() const { return IFacade::instance()->notice(); } object mManager; }; // exception handling void translate(error const& e) { PyErr_SetString(PyExc_AttributeError, e._msg.c_str()); } // utility functions PyObject* _last; void dumpLast() { std::cout << "dumpLast" << std::endl; std::cout << " last: " << (void*)_last << " [" << (typeid(*_last)).name() << "]" << std::endl; std::cout << " last->ob_refcnt: " << _last->ob_refcnt << std::endl; std::cout << " last->ob_type->tp_name: " << _last->ob_type->tp_name << std::endl; } void dumpPyObject(PyObject* pyobject) { _last = pyobject; // steal for dumpLast std::cout << "dumpPyObject" << std::endl; std::cout << " pyobject: " << (void*)pyobject << " [" << (typeid(*pyobject)).name() << "]" << std::endl; std::cout << " pyobject->ob_refcnt: " << pyobject->ob_refcnt << std::endl; std::cout << " pyobject->ob_type->tp_name: " << pyobject->ob_type->tp_name << std::endl; } void dumpProduct(ProductProxy* proxy) { std::cout << "dumpProduct" << std::endl; std::cout << " proxy: " << (void*)proxy << " [" << (typeid(*proxy)).name() << "]" << std::endl; ProductBase* base = dynamic_cast<ProductBase*>(proxy); if (base) { std::cout << " proxy->mSelf: " << (void*)base->mSelf << " [" << (typeid(*base->mSelf)).name() << "]" << std::endl; std::cout << " proxy->mSelf->ob_refcnt: " << base->mSelf->ob_refcnt << std::endl; std::cout << " proxy->mSelf->ob_type->tp_name: " << base->mSelf->ob_type->tp_name << std::endl; } else { std::cout << " proxy->mProduct: " << (void*)proxy->mProduct << " [" << (typeid(*proxy->mProduct)).name() << "]" << std::endl; } } int useValue_PyObject_ptr(PyObject* product) { return call_method<int>(product, "value"); } int useValue_object_ref(object& product) { return call_method<int>(product.ptr(), "value"); } int useValue_ProductProxy_ptr(ProductProxy* product) { return NULL != product ? product->value() : -1; } ProductProxy* passBack_ProductProxy_ptr(ProductProxy* product) { return product; } object passBack_object(object& product) { ProductProxy* proxy = arg_from_python<ProductProxy*>(product.ptr())(product.ptr()); if (NULL == proxy) return object(); else return product; } BOOST_PYTHON_MODULE(abcdf_ext) { register_exception_translator<error>(&translate); class_<ProductProxy, ProductBase, boost::noncopyable>("IProduct") .def("value", &ProductProxy::value, &ProductBase::default_value, "Returns an int value") .def("set", &ProductProxy::set, &ProductBase::default_set, "Sets an int value") .def("other", &ProductProxy::otherWrap, &ProductBase::default_other, "Returns an int value using another IProduct") ; class_<ManagerProxy, ManagerBase, boost::noncopyable>("IManager") .def("create", &ManagerProxy::createWrap, &ManagerBase::default_create) .def("modify", &ManagerProxy::modifyWrap, &ManagerBase::default_modify) .def("store", &ManagerProxy::storeWrap, &ManagerBase::default_store) .def("retrieve", &ManagerProxy::retrieveWrap, &ManagerBase::default_retrieve) ; class_<FacadeProxy>("IFacade", no_init) .def("instance", &FacadeProxy::instance, return_value_policy<manage_new_object>()) // How do I do a singleton? .staticmethod("instance") .def("manager", &FacadeProxy::managerWrap) .def("setManager", &FacadeProxy::setManagerWrap) // ,with_custodian_and_ward<1, 2>()) // I don't think I need this as returning an object keeps track of reference counts. .def("update", &FacadeProxy::update) .def("notice", &FacadeProxy::notice) ; def("dumpLast", &dumpLast); def("dumpPyObject", &dumpPyObject); def("dumpProduct", &dumpProduct); def("useValue_PyObject_ptr", &useValue_PyObject_ptr); def("useValue_object_ref", &useValue_object_ref); def("useValue_ProductProxy_ptr", &useValue_ProductProxy_ptr); def("ProductProxy_ptr_manage_new_object", &passBack_ProductProxy_ptr, return_value_policy<manage_new_object>()); def("ProductProxy_ptr_reference_existing_object", &passBack_ProductProxy_ptr, return_value_policy<reference_existing_object>()); def("Product_as_object", &passBack_object); // no return_value_policy needed } #include "../../../boost_1_30_0/libs/python/test/module_tail.cpp" ============ abcdf_ext.cpp ==================================================== # test abcdf_ext: Abstract Base Class with DeFaults from abcdf_ext import * class Derived(IProduct): def __init__(self, i): IProduct.__init__(self) self.i = i def value(self): return self.i def set(self, i): self.i = i def other(self, product): return self.i*1000 + product.value() def callValue(product): return product.value() def callOther(product, other): return product.other(other) def callSet(product, i): product.set(i) class DManager(IManager): def __init__(self): IManager.__init__(self) self._products = [] def create(self, i): return Derived(i) def modify(self, product): product.set(product.value()*3) return product def store(self, product): index = len(self._products) self._products.append(product) return index def retrieve(self, index): try: return self._products[index] except: return None E=IFacade.instance() M=E.manager() D=DManager() m = M.create(2) n = M.create(3) m._m = "m" n._n = "n" i1 = M.store(m) i2 = M.store(n) i3 = M.store(M.create(4)) M.retrieve(i1)._m d = D.create(4) E.setManager(D) Dr=E.manager() e=Dr.create(5) f=Dr.create(6) e._e = "e" f._f = "f" Dr.store(e) Dr.store(f) =============================================================================== ===============================================================================

2 1

Problem with current pyste and inheritance
by Gideon May Feb. 16, 2004

Feb. 16, 2004

Hi, I've got a C++ class hierarchy which looks like this: Base ^ | Derived ^ | Sub and I want to use pyste to generate python bindings. I've got it working except for the fact that the bindings for Derived are being defined twice by pyste. I've attached the include files and pyste files. I generate the code with the following command: pyste --module=double Base.pyste Derived.pyste Sub.pyste Any suggestions ? Thanks, Gideon

3 2

re: implicitly_convertible
by aashish Feb. 5, 2004

Feb. 5, 2004

Hi, I have this porgram where I need to convert a python float in to C++ class object and for that I am using implicitly_convertible In the porgram below (a very simple one) the constructor takd two arguments and when I compile with that I got this error .. c:\users\aashish\boost-1.30.2\boost\python\converter\implicit.hpp(34): error C2664: 'PlotVariableTable::PlotVariableTable(const PlotVariableTable &)' : cannot convert parameter 1 from 'const double' to 'const PlotVariableTable &' Now when I compiled and tested with the constructor taking only a single value (and hence changed some lines accordingly) program just worked fine. Please let know is someone can help me as soon as possible. Thanks, Aashish #include <boost/any.hpp> #include <boost/python.hpp> #include <boost/python/extract.hpp> #include <boost/python/dict.hpp> #include <boost/any.hpp> #include <boost/python/implicit.hpp> #include <boost/python/module.hpp> #include <cstdio> #include<iostream> //#include <PlotVariableTable.h> using namespace boost::python; namespace bp = boost::python; class PlotVariableTable { public: /** * Default Constructor * * @param cols number of columns in the table */ PlotVariableTable(double rows, double cols):v(rows), v1(cols){} double v, v1; }; PlotVariableTable make_x(double n, double n1) { PlotVariableTable a = PlotVariableTable( n , n1); return a; } BOOST_PYTHON_MODULE(hello) { def("make_x",make_x); class_<PlotVariableTable>("PlotVariableTable",init<double, double>()); implicitly_convertible<double,PlotVariableTable>(); }

3 7

New slice implementation
by Jonathan Brandmeyer Feb. 3, 2004

Feb. 3, 2004

I have written a new implementation for free-standing slice objects. This allows you to create and query slice objects that include a step-size, as well as export a form of __getitem__ and/or __setitem__ that can receive slice arguments and tuples of slice arguments. Originally I needed this type for multidimensional slicing of Numeric arrays, but I decided to round out the type, boostify it, and pass it along. Dave, please let me know if there is anything you need me to do to make this meet your standards for acceptance into Boost.Python. I should be able to answer any questions you might have as early as late tomorrow night or Wednesday. -Jonathan Brandmeyer

5 25

Manipulating arguments with CallPolicies::precall?
by Arve Knudsen Feb. 3, 2004

Feb. 3, 2004

Hi I want to wrap a native C Python object in a C++ object that takes care of constructing and destructing it properly (there isn't any way to specify custom allocation/deallocation routines are there?). However, I would like to send this object directly to the associated routines (its part of an existing Python extension). I haven't found any direct support for this kind of thing within boost::python, since everything seems strongly tied to the contained type (my wrapping C++ class). But, I figured it might be possible to manipulate the Python argument tuple within CallPolicies::precall? So I experimented a little and it seems I am able to change the first argument to point to the contained C object, instead of it's wrapper. But, when the function (which takes a pointer to one such C object) receives the object something is not right. A member which was initialized to zero (verified within caller.hpp), now contains some other number. I suppose some conversion magic goes wrong? I've tried to figure out what's going on myself, but gdb tends to die on me in the process (no pun intended). It'd be great if someone could enlighten me as to why this won't work (fingers crossed), or perhaps present a better solution :) Btw, I'm getting lots of warnings building boost::python from CVS (this is on Linux with GCC 3.3.2 and Python 2.3), because of this: /usr/include/python2.3/pyconfig.h:847:1: warning: "_POSIX_C_SOURCE" redefined. Is Python 2.3 to blame? I dont think I ever saw this warning with boost 1.30.2, though. Thanks Arve Knudsen

2 2

Operator== for reflected enums can return True when it shouldn't?
by Pete Bartlett Feb. 3, 2004

Feb. 3, 2004

(Apologies if this issue has been raised before - I must have put the wrong search terms into Google) On my setup (Python 2.3, boost-cvs from early December, MSVC 7.1), Python returns True when comparing two reflected enums of different type that have the same internal integer representation. Though I am sure it is bad Python style to compare different types, would it right and possible to return False in this case? Pete Minimal example: //Cpp: #include <boost/python/enum.hpp> enum e_A{e_a}; //e_a has "internal value" 0 enum e_B{e_b}; //e_b has "internal value" 0 BOOST_PYTHON_MODULE( enum_test ) { using namespace boost::python; enum_<e_A>("e_A").value("e_a",e_a); enum_<e_B>("e_B").value("e_b",e_b); } //Python >>>import enum_test >>>print (enum_test.e_A.e_a == enum_test.e_B.e_b ) True

2 1

Problem with pickling returning a boost::python::dict object
by Pierre Barbier de Reuille Feb. 3, 2004

Feb. 3, 2004

I want to enable picking as if the data stored in C++ were stored in python variables. To do so, I get the __dict__ variable of my object, add the variables I want to save in the pickling and return the modified dictionnary. But then I have the error : Traceback (most recent call last): File "<string>", line 1, in ? cPickle.PicklingError: Can't pickle <type 'Boost.Python.instance'>: import of module Boost.Python failed 'g' being on object want to pickle : >>> d = g.__getstate__() >>> d.__class__ <type 'dict'> Here is my __getstate__ picklink function (I use boost pickling method ... ): struct CellGraph3D_pickle_suite : boost::python::pickle_suite { /* ... */ static boost::python::dict getstate(boost::python::object c_obj) { using namespace boost::python; CellGraph3D & c = extract<CellGraph3D &>(c_obj)(); dict save = extract<dict>( c_obj.attr( "__dict__" ) ); save[ "_vertices_" ] = c.getVertices(); save[ "_edges_" ] = c.getEdges(); save[ "_positions_" ] = c.pos_map; save[ "_cells_" ] = c.cell_map; save[ "_colors_" ] = c.color_map; return save; } /* ... */ } If, instead of returning a dict I return a tuple, it seems to work, but that's not what I want. Thanks, -- Pierre Barbier de Reuille INRA - UMR Cirad/Inra/Cnrs/Univ.MontpellierII AMAP Botanique et Bio-informatique de l'Architecture des Plantes TA40/PSII, Boulevard de la Lironde 34398 MONTPELLIER CEDEX 5, France tel : (33) 4 67 61 65 77 fax : (33) 4 67 61 56 68

3 3

iterator interface question
by Neal D. Becker Feb. 1, 2004

Feb. 1, 2004

How to I interface algorithms with STL style iterator interface to python? For example: typedef std::complex<double> Complex; //expose std::vector<Complex> to python: //also let's pick a simple example function: inline Complex Sum (const std::vector<Complex>::iterator& beg, const std::vector<Complex>::iterator& end) { Complex sum = 0; return std::accumulate (beg, end, sum); } BOOST_PYTHON_MODULE(Test) { class_<std::vector<std::complex<double> > >("CVec") .def(init<size_t>()) .def(vector_indexing_suite<std::vector<std::complex<double> >, true >()) ; def ("accumulate", Sum); } Actually 2 questions: 1) How do I call accumulate from python? 2) (really a c++ question) How can I avoid introducing the "Sum" function? If I put def ("accumulate", std::accumulate<const std::vector<Complex>::iterator&, Complex>) I get Test.cc:115: error: no matching function for call to `def(const char[11], <unknown type>)' Problem is it's overloaded, I guess, but I don't know what to do.

4 10