Std::Vector to Boost::Python::List

std::vector to boost::python::list

I have this function using iterators to convert std::vector to py::list:

namespace py = boost::python;

template<class T>
py::list std_vector_to_py_list(const std::vector<T>& v)
{
    py::object get_iter = py::iterator<std::vector<T> >();
    py::object iter = get_iter(v);
    py::list l(iter);
    return l;
}

Using boost::python, how to return vector of structs as list of dicts to Python?

In the end I adopted a solution like the following, which I post here in case it is useful to somebody else in the future. This can be improved by adding boost's "readonly" qualifier, but I haven't done so yet.

#include <boost/python.hpp>
using namespace boost::python;

struct Point { 
    int x, y;
};

using Points = std::vector<Point>;

struct Converter
{
    static PyObject* convert(const Points& v)
    {
        boost::python::list ret;
        for (const auto& c : v) {
            boost::python::dict *r = new boost::python::dict();
            (*r)["x"] = c.x;
            (*r)["y"] = c.y;
            ret.append(boost::python::object(*r));
         }
        return boost::python::incref(ret.ptr());
    }
};

BOOST_PYTHON_MODULE(mymodule)
{
    boost::python::to_python_converter<Points, Converter>();

    class_<MyClass, boost::noncopyable>("MyClass")
        .def("get_data", &MyClass::get_data);
}

boost::python: Python list to std::vector

To make your C++ method accept Python lists you should use boost::python::list

void massadd(boost::python::list& ns)
{
    for (int i = 0; i < len(ns); ++i)
    {
        add(boost::python::extract<double>(ns[i]));
    }
}

Exposing std::vector struct with boost.python

Method .def("get_vector",&myName::myfoo::get_vector) is not working because it returns a pointer to a vector, so it's necessary to inform the policy that defines how object ownership should be managed:

class_<myName::myfoo>("myfoo", no_init)
   // current code
   .def("get_vector", &myfoo::get_vector, return_value_policy<reference_existing_object>())
;

In order to use vector_indexing_suite, it is necessary to implement the equal to operator to the class that it holds:

struct sFOO
{
    unsigned int start = 3 ;
    double foo = 20.0 ;

    bool operator==(const sFOO& rhs)
    {
        return this == &rhs; //< implement your own rules.
    }
};

then you can export the vector:

#include <boost/python/suite/indexing/vector_indexing_suite.hpp>

class_<std::vector<sFOO>>("vector_sFOO_")
   .def(vector_indexing_suite<std::vector<sFOO>>())
;

Passing Python list to C++ vector using Boost.python

Assuming you have function that takes a std::vector<Foo>

void bar (std::vector<Foo> arg)

The easiest way to handle this is to expose the vector to python.

BOOST_PYTHON_MODULE(awesome_module)
{
    class_<Foo>("Foo")
        //methods and attrs here
    ;

    class_<std::vector<Foo> >("VectorOfFoo")
        .def(vector_indexing_suite<std::vector<foo> >() )
    ;

    .def("bar", &bar)
}

So now in python we can stick Foos into a vector and pass the vector to bar

from awesome_module import *
foo_vector = VectorOfFoo()
foo_vector.extend(Foo(arg) for arg in arglist)
bar(foo_vector)

Wrapping an std::vector using boost::python vector_indexing_suite

Due to the semantic differences between the languages, it is often very difficult to apply a single reusable solution to all scenarios when collections are involved. The largest issue is that the while Python collections directly support references, C++ collections require a level of indirection, such as by having shared_ptr element types. Without this indirection, C++ collections will not be able to support the same functionality as Python collections. For instance, consider two indexes that refer to the same object:

s = Spam()
spams = []
spams.append(s)
spams.append(s)

Without pointer-like element types, a C++ collection could not have two indexes referring to the same object. Nevertheless, depending on usage and needs, there may be options that allow for a Pythonic-ish interface for the Python users while still maintaining a single implementation for C++.

• The most Pythonic solution would be to use a custom converter that would convert a Python iterable object to a C++ collection. See this answer for implementation details. Consider this option if:
  
  
  • The collection's elements are cheap to copy.
  • The C++ functions operate only on rvalue types (i.e., std::vector<> or const std::vector<>&). This limitation prevents C++ from making changes to the Python collection or its elements.
• Enhance vector_indexing_suite capabilities, reusing as many capabilities as possible, such as its proxies for safely handling index deletion and reallocation of the underlying collection:
  
  
  • Expose the model with a custom HeldType that functions as a smart pointer and delegate to either the instance or the element proxy objects returned from vector_indexing_suite.
  • Monkey patch the collection's methods that insert elements into the collection so that the custom HeldType will be set to delegate to a element proxy.

---

When exposing a class to Boost.Python, the HeldType is the type of object that gets embedded within a Boost.Python object. When accessing the wrapped types object, Boost.Python invokes get_pointer() for the HeldType. The object_holder class below provides the ability to return a handle to either an instance it owns or to an element proxy:

/// @brief smart pointer type that will delegate to a python
///        object if one is set.
template <typename T>
class object_holder
{
public:

  typedef T element_type;

  object_holder(element_type* ptr)
    : ptr_(ptr),
      object_()
  {}

  element_type* get() const
  {
    if (!object_.is_none())
    {
      return boost::python::extract<element_type*>(object_)();
    }
    return ptr_ ? ptr_.get() : NULL;
  }

  void reset(boost::python::object object)
  {
    // Verify the object holds the expected element.
    boost::python::extract<element_type*> extractor(object_);
    if (!extractor.check()) return;

    object_ = object;
    ptr_.reset();
  }

private:
  boost::shared_ptr<element_type> ptr_;
  boost::python::object object_;
};

/// @brief Helper function used to extract the pointed to object from
///        an object_holder.  Boost.Python will use this through ADL.
template <typename T>
T* get_pointer(const object_holder<T>& holder)
{
  return holder.get();
}

With the indirection supported, the only thing remaining is patching the collection to set the object_holder. One clean and reusable way to support this is to use def_visitor. This is a generic interface that allows for class_ objects to be extended non-intrusively. For instance, the vector_indexing_suite uses this capability.

The custom_vector_indexing_suite class below monkey patches the append() method to delegate to the original method, and then invokes object_holder.reset() with a proxy to the newly set element. This results in the object_holder referring to the element contained within the collection.

/// @brief Indexing suite that will resets the element's HeldType to
///        that of the proxy during element insertion.
template <typename Container,
          typename HeldType>
class custom_vector_indexing_suite
  : public boost::python::def_visitor<
      custom_vector_indexing_suite<Container, HeldType>>
{
private:

  friend class boost::python::def_visitor_access;

  template <typename ClassT>
  void visit(ClassT& cls) const
  {
    // Define vector indexing support.
    cls.def(boost::python::vector_indexing_suite<Container>());

    // Monkey patch element setters with custom functions that
    // delegate to the original implementation then obtain a 
    // handle to the proxy.
    cls
      .def("append", make_append_wrapper(cls.attr("append")))
      // repeat for __setitem__ (slice and non-slice) and extend
      ;
  }

  /// @brief Returned a patched 'append' function.
  static boost::python::object make_append_wrapper(
    boost::python::object original_fn)
  {
    namespace python = boost::python;
    return python::make_function([original_fn](
          python::object self,
          HeldType& value)
        {
          // Copy into the collection.
          original_fn(self, value.get());
          // Reset handle to delegate to a proxy for the newly copied element.
          value.reset(self[-1]);
        },
      // Call policies.
      python::default_call_policies(),
      // Describe the signature.
      boost::mpl::vector<
        void,           // return
        python::object, // self (collection)
        HeldType>()     // value
      );
  }
};

Wrapping needs to occur at runtime and custom functor objects cannot be directly defined on the class via def(), so the make_function() function must be used. For functors, it requires both CallPolicies and a MPL front-extensible sequence representing the signature.

---

Here is a complete example that demonstrates using the object_holder to delegate to proxies and custom_vector_indexing_suite to patch the collection.

#include <boost/python.hpp>
#include <boost/python/suite/indexing/vector_indexing_suite.hpp>

/// @brief Mockup type.
struct spam
{
  int val;

  spam(int val) : val(val) {}
  bool operator==(const spam& rhs) { return val == rhs.val; }
};

/// @brief Mockup function that operations on a collection of spam instances.
void modify_spams(std::vector<spam>& spams)
{
  for (auto& spam : spams)
    spam.val *= 2;
}

/// @brief smart pointer type that will delegate to a python
///        object if one is set.
template <typename T>
class object_holder
{
public:

  typedef T element_type;

  object_holder(element_type* ptr)
    : ptr_(ptr),
      object_()
  {}

  element_type* get() const
  {
    if (!object_.is_none())
    {
      return boost::python::extract<element_type*>(object_)();
    }
    return ptr_ ? ptr_.get() : NULL;
  }

  void reset(boost::python::object object)
  {
    // Verify the object holds the expected element.
    boost::python::extract<element_type*> extractor(object_);
    if (!extractor.check()) return;

    object_ = object;
    ptr_.reset();
  }

private:
  boost::shared_ptr<element_type> ptr_;
  boost::python::object object_;
};

/// @brief Helper function used to extract the pointed to object from
///        an object_holder.  Boost.Python will use this through ADL.
template <typename T>
T* get_pointer(const object_holder<T>& holder)
{
  return holder.get();
}

/// @brief Indexing suite that will resets the element's HeldType to
///        that of the proxy during element insertion.
template <typename Container,
          typename HeldType>
class custom_vector_indexing_suite
  : public boost::python::def_visitor<
      custom_vector_indexing_suite<Container, HeldType>>
{
private:

  friend class boost::python::def_visitor_access;

  template <typename ClassT>
  void visit(ClassT& cls) const
  {
    // Define vector indexing support.
    cls.def(boost::python::vector_indexing_suite<Container>());

    // Monkey patch element setters with custom functions that
    // delegate to the original implementation then obtain a 
    // handle to the proxy.
    cls
      .def("append", make_append_wrapper(cls.attr("append")))
      // repeat for __setitem__ (slice and non-slice) and extend
      ;
  }

  /// @brief Returned a patched 'append' function.
  static boost::python::object make_append_wrapper(
    boost::python::object original_fn)
  {
    namespace python = boost::python;
    return python::make_function([original_fn](
          python::object self,
          HeldType& value)
        {
          // Copy into the collection.
          original_fn(self, value.get());
          // Reset handle to delegate to a proxy for the newly copied element.
          value.reset(self[-1]);
        },
      // Call policies.
      python::default_call_policies(),
      // Describe the signature.
      boost::mpl::vector<
        void,           // return
        python::object, // self (collection)
        HeldType>()     // value
      );
  }

  // .. make_setitem_wrapper
  // .. make_extend_wrapper
};

BOOST_PYTHON_MODULE(example)
{
  namespace python = boost::python;

  // Expose spam.  Use a custom holder to allow for transparent delegation
  // to different instances.
  python::class_<spam, object_holder<spam>>("Spam", python::init<int>())
    .def_readwrite("val", &spam::val)
    ;

  // Expose a vector of spam.
  python::class_<std::vector<spam>>("SpamVector")
    .def(custom_vector_indexing_suite<
      std::vector<spam>, object_holder<spam>>())
    ;

  python::def("modify_spams", &modify_spams);
}

Interactive usage:

>>> import example
>>> spam = example.Spam(5)
>>> spams = example.SpamVector()
>>> spams.append(spam)
>>> assert(spams[0].val == 5)
>>> spam.val = 21
>>> assert(spams[0].val == 21)
>>> example.modify_spams(spams)
>>> assert(spam.val == 42)
>>> spams.append(spam)
>>> spam.val = 100
>>> assert(spams[1].val == 100)
>>> assert(spams[0].val == 42) # The container does not provide indirection.

As the vector_indexing_suite is still being used, the underlying C++ container should only be modified using the Python object's API. For instance, invoking push_back on the container may cause a reallocation of the underlying memory and cause problems with existing Boost.Python proxies. On the other hand, one can safely modify the elements themselves, such as was done via the modify_spams() function above.

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