Boost.Python

Contents

Introduction

Interface

indexing_suite

indexing_suite sub-classes

vector_indexing_suite

indexing_suite class

vector_indexing_suite class

Introduction

Indexing is a Boost Python facility for easy exportation of indexable C++ containers to Python. Indexable containers are containers that allow random access through the operator[] (e.g. std::vector).

While Boost Python has all the facilities needed to expose indexable C++ containers such as the ubiquitous std::vector to Python, the procedure is not as straightforward as we'd like it to be. Python containers do not map easily to C++ containers. Emulating Python containers in C++ (see Python Reference Manual, Emulating container types) using Boost Python is non trivial. There are a lot of issues to consider before we can map a C++ container to Python. These involve implementing wrapper functions for the methods __len__, __getitem__, __setitem__, __delitem__, __iter__ and __contains.

The goals:

• Make indexable C++ containers behave exactly as one would expect a Python container to behave.
• Provide default reference semantics for container element indexing (__getitem__) such that c[i] can be mutable. Require:

      val = c[i]
      c[i].m()
      val == c[i]
            

  where m is a non-const (mutating) member function (method).
• Return safe references from __getitem__ such that subsequent adds and deletes to and from the container will not result in dangling references (will not crash Python).
• Support slice indexes.
• Accept Python container arguments (e.g. lists, tuples) wherever appropriate.
• Allow for extensibility through re-definable policy classes.
• Provide predefined support for the most common STL and STL like indexable containers.

The Boost.Python Indexing Interface

indexing_suite [ Header <boost/python/indexing/indexing_suite.hpp> ]

The indexing_suite class is the base protocol class for the management of C++ containers intended to be integrated to Python. The objective is make a C++ container look and feel and behave exactly as we'd expect a Python container. The class automatically wraps these special Python methods (taken from the Python reference: Emulating container types):

__len__(self)

Called to implement the built-in function len()  Should return the length of the object, an integer >= 0. Also, an object that doesn't define a __nonzero__() method and whose __len__() method returns zero is considered to be false in a Boolean context.  

__getitem__(self, key)

Called to implement evaluation of self[key]. For sequence types, the accepted keys should be integers and slice objects.  Note that the special interpretation of negative indexes (if the class wishes to emulate a sequence type) is up to the __getitem__() method. If key is of an inappropriate type, TypeError may be raised; if of a value outside the set of indexes for the sequence (after any special interpretation of negative values), IndexError should be raised. Note: for loops expect that an IndexError will be raised for illegal indexes to allow proper detection of the end of the sequence.

__setitem__(self, key, value)

Called to implement assignment to self[key]. Same note as for __getitem__(). This should only be implemented for mappings if the objects support changes to the values for keys, or if new keys can be added, or for sequences if elements can be replaced. The same exceptions should be raised for improper key values as for the __getitem__() method.

__delitem__(self, key)

Called to implement deletion of self[key]. Same note as for __getitem__(). This should only be implemented for mappings if the objects support removal of keys, or for sequences if elements can be removed from the sequence. The same exceptions should be raised for improper key values as for the __getitem__() method.

__iter__(self)

This method is called when an iterator is required for a container. This method should return a new iterator object that can iterate over all the objects in the container. For mappings, it should iterate over the keys of the container, and should also be made available as the method iterkeys().

Iterator objects also need to implement this method; they are required to return themselves. For more information on iterator objects, see ``Iterator Types'' in the Python Library Reference.

__contains__(self, item)

Called to implement membership test operators. Should return true if item is in self, false otherwise. For mapping objects, this should consider the keys of the mapping rather than the values or the key-item pairs.

indexing_suite sub-classes

The indexing_suite is not meant to be used as is. A couple of policy functions must be supplied by subclasses of indexing_suite. However, a set of indexing_suite subclasses for the standard indexable STL containers will be provided, In most cases, we can simply use the available predefined suites. In some cases, we can refine the predefined suites to suit our needs.

vector_indexing_suite [ Header <boost/python/indexing/vector_indexing_suite.hpp> ]

The vector_indexing_suite class is a predefined indexing_suite derived class designed to wrap std::vector (and std::vector like [i.e. a class with std::vector interface]) classes (currently, this is the only predefined suite available). It provides all the policies required by the indexing_suite.

Example usage:

    class X {...};
    ...

    class_<std::vector<X> >("XVec")
        .def(vector_indexing_suite<std::vector<X> >())
    ;

XVec is now a full-fledged Python container (see the example in full, along with its python test).

indexing_suite class

indexing_suite<
class Container
, class DerivedPolicies
, bool NoProxy
, class Element
, class Key
, class Index

    template <
          class Container
        , class DerivedPolicies
        , bool NoProxy = false
        , class Element = typename Container::value_type
        , class Key = typename Container::value_type
        , class Index = typename Container::size_type
    >
    class indexing_suite
        : unspecified
    {
    public:

        indexing_suite(); // default constructor
    }
    

DerivedPolicies

Derived classes provide the hooks needed by theindexing_suite:

        static element_type&
        get_item(Container& container, index_type i);

        static object
        get_slice(Container& container, index_type from, index_type to);

        static void
        set_item(Container& container, index_type i, element_type const& v);

        static void
        set_slice(
            Container& container, index_type from,
            index_type to, element_type const& v
        );

        template <class Iter>
        static void
        set_slice(Container& container, index_type from,
            index_type to, Iter first, Iter last
        );

        static void
        delete_item(Container& container, index_type i);

        static void
        delete_slice(Container& container, index_type from, index_type to);

        static size_t
        size(Container& container);

        template <class T>
        static bool
        contains(Container& container, T const& val);

        static index_type
        convert_index(Container& container, PyObject* i);

        static index_type
        adjust_index(index_type current, index_type from,
            index_type to, size_type len
        );

Most of these policies are self explanatory. However, convert_index and adjust_index deserve some explanation.

convert_index converts a Python index into a C++ index that the container can handle. For instance, negative indexes in Python, by convention, start counting from the right(e.g. C[-1] indexes the rightmost element in C). convert_index should handle the necessary conversion for the C++ container (e.g. convert -1 to C.size()-1). convert_index should also be able to convert the type of the index (A dynamic Python type) to the actual type that the C++ container expects.

When a container expands or contracts, held indexes to its elements must be adjusted to follow the movement of data. For instance, if we erase 3 elements, starting from index 0 from a 5 element vector, what used to be at index 4 will now be at index 1:

    [a][b][c][d][e] ---> [d][e]
                 ^           ^
                 4           1

adjust_index takes care of the adjustment. Given a current index, the function should return the adjusted index when data in the container at index from..to is replaced by len elements.

    template <
        class Container,
        bool NoProxy = false,
        class DerivedPolicies = unspecified_default
    class vector_indexing_suite
        : public indexing_suite<Container, DerivedPolicies, NoProxy>
    {
    public:

        typedef typename Container::value_type element_type;
        typedef typename Container::value_type key_type;
        typedef typename Container::size_type index_type;
        typedef typename Container::size_type size_type;
        typedef typename Container::difference_type difference_type;
    
        static element_type&
        get_item(Container& container, index_type i);

        static object
        get_slice(Container& container, index_type from, index_type to);

        static void
        set_item(Container& container, index_type i, element_type const& v);

        static void
        set_slice(Container& container, index_type from, 
            index_type to, element_type const& v);

        template <class Iter>
        static void
        set_slice(Container& container, index_type from,
            index_type to, Iter first, Iter last);

        static void 
        delete_item(Container& container, index_type i);

        static void 
        delete_slice(Container& container, index_type from, index_type to);
     
        static size_t
        size(Container& container);
     
        static bool
        contains(Container& container, key_type const& key);
     
        static index_type
        convert_index(Container& container, PyObject* i);
     
        static index_type
        adjust_index(index_type current, index_type from, 
            index_type to, size_type len);
    };