tutorial.qbk

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    def("f", f,
        return_internal_reference<1,
            with_custodian_and_ward<1, 2> >());

What are the [^1] and [^2] parameters, you ask?

    return_internal_reference<1

Informs Boost.Python that the first argument, in our case [^Y& y], is the
owner of the returned reference: [^X&]. The "[^1]" simply specifies the
first argument. In short: "return an internal reference [^X&] owned by the
1st argument [^Y& y]".

    with_custodian_and_ward<1, 2>

Informs Boost.Python that the lifetime of the argument indicated by ward
(i.e. the 2nd argument: [^Z* z]) is dependent on the lifetime of the
argument indicated by custodian (i.e. the 1st argument: [^Y& y]).

It is also important to note that we have defined two policies above. Two
or more policies can be composed by chaining. Here's the general syntax:

    policy1<args...,
        policy2<args...,
            policy3<args...> > >

Here is the list of predefined call policies. A complete reference detailing
these can be found [@../../../v2/reference.html#models_of_call_policies here].

* [*with_custodian_and_ward]:  Ties lifetimes of the arguments
* [*with_custodian_and_ward_postcall]:  Ties lifetimes of the arguments and results
* [*return_internal_reference]:  Ties lifetime of one argument to that of result
* [*return_value_policy<T> with T one of:]
    * [*reference_existing_object]: naive (dangerous) approach
    * [*copy_const_reference]: Boost.Python v1 approach
    * [*copy_non_const_reference]:
    * [*manage_new_object]: Adopt a pointer and hold the instance

[blurb :-) [*Remember the Zen, Luke:]

"Explicit is better than implicit"

"In the face of ambiguity, refuse the temptation to guess"
]

[endsect]
[section Overloading]

The following illustrates a scheme for manually wrapping an overloaded
member functions. Of course, the same technique can be applied to wrapping
overloaded non-member functions.

We have here our C++ class:

    struct X
    {
        bool f(int a)
        {
            return true;
        }

        bool f(int a, double b)
        {
            return true;
        }

        bool f(int a, double b, char c)
        {
            return true;
        }

        int f(int a, int b, int c)
        {
            return a + b + c;
        };
    };

Class X has 4 overloaded functions. We will start by introducing some
member function pointer variables:

    bool    (X::*fx1)(int)              = &X::f;
    bool    (X::*fx2)(int, double)      = &X::f;
    bool    (X::*fx3)(int, double, char)= &X::f;
    int     (X::*fx4)(int, int, int)    = &X::f;

With these in hand, we can proceed to define and wrap this for Python:

    .def("f", fx1)
    .def("f", fx2)
    .def("f", fx3)
    .def("f", fx4)

[endsect]
[section Default Arguments]

Boost.Python wraps (member) function pointers. Unfortunately, C++ function
pointers carry no default argument info. Take a function [^f] with default
arguments:

    int f(int, double = 3.14, char const* = "hello");

But the type of a pointer to the function [^f] has no information
about its default arguments:

    int(*g)(int,double,char const*) = f;    // defaults lost!

When we pass this function pointer to the [^def] function, there is no way
to retrieve the default arguments:

    def("f", f);                            // defaults lost!

Because of this, when wrapping C++ code, we had to resort to manual
wrapping as outlined in the [link python.overloading previous section], or
writing thin wrappers:

    // write "thin wrappers"
    int f1(int x) { f(x); }
    int f2(int x, double y) { f(x,y); }

    /*...*/

        // in module init
        def("f", f);  // all arguments
        def("f", f2); // two arguments
        def("f", f1); // one argument

When you want to wrap functions (or member functions) that either:

* have default arguments, or
* are overloaded with a common sequence of initial arguments

[h2 BOOST_PYTHON_FUNCTION_OVERLOADS]

Boost.Python now has a way to make it easier. For instance, given a function:

    int foo(int a, char b = 1, unsigned c = 2, double d = 3)
    {
        /*...*/
    }

The macro invocation:

    BOOST_PYTHON_FUNCTION_OVERLOADS(foo_overloads, foo, 1, 4)

will automatically create the thin wrappers for us. This macro will create
a class [^foo_overloads] that can be passed on to [^def(...)]. The third
and fourth macro argument are the minimum arguments and maximum arguments,
respectively. In our [^foo] function the minimum number of arguments is 1
and the maximum number of arguments is 4. The [^def(...)] function will
automatically add all the foo variants for us:

    def("foo", foo, foo_overloads());

[h2 BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS]

Objects here, objects there, objects here there everywhere. More frequently
than anything else, we need to expose member functions of our classes to
Python. Then again, we have the same inconveniences as before when default
arguments or overloads with a common sequence of initial arguments come
into play. Another macro is provided to make this a breeze.

Like [^BOOST_PYTHON_FUNCTION_OVERLOADS],
[^BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS] may be used to automatically create
the thin wrappers for wrapping member functions. Let's have an example:

    struct george
    {
        void
        wack_em(int a, int b = 0, char c = 'x')
        {
            /*...*/
        }
    };

The macro invocation:

    BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(george_overloads, wack_em, 1, 3)

will generate a set of thin wrappers for george's [^wack_em] member function
accepting a minimum of 1 and a maximum of 3 arguments (i.e. the third and
fourth macro argument). The thin wrappers are all enclosed in a class named
[^george_overloads] that can then be used as an argument to [^def(...)]:

    .def("wack_em", &george::wack_em, george_overloads());

See the [@../../../v2/overloads.html#BOOST_PYTHON_FUNCTION_OVERLOADS-spec overloads reference]
for details.

[h2 init and optional]

A similar facility is provided for class constructors, again, with
default arguments or a sequence of overloads. Remember [^init<...>]? For example,
given a class X with a constructor:

    struct X
    {
        X(int a, char b = 'D', std::string c = "constructor", double d = 0.0);
        /*...*/
    }

You can easily add this constructor to Boost.Python in one shot:

    .def(init<int, optional<char, std::string, double> >())

Notice the use of [^init<...>] and [^optional<...>] to signify the default
(optional arguments).

[endsect]
[section Auto-Overloading]

It was mentioned in passing in the previous section that
[^BOOST_PYTHON_FUNCTION_OVERLOADS] and [^BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS]
can also be used for overloaded functions and member functions with a
common sequence of initial arguments. Here is an example:

     void foo()
     {
        /*...*/
     }

     void foo(bool a)
     {
        /*...*/
     }

     void foo(bool a, int b)
     {
        /*...*/
     }

     void foo(bool a, int b, char c)
     {
        /*...*/
     }

Like in the previous section, we can generate thin wrappers for these
overloaded functions in one-shot:

    BOOST_PYTHON_FUNCTION_OVERLOADS(foo_overloads, foo, 0, 3)

Then...

    .def("foo", (void(*)(bool, int, char))0, foo_overloads());

Notice though that we have a situation now where we have a minimum of zero
(0) arguments and a maximum of 3 arguments.

[h2 Manual Wrapping]

It is important to emphasize however that [*the overloaded functions must
have a common sequence of initial arguments]. Otherwise, our scheme above
will not work. If this is not the case, we have to wrap our functions
[link python.overloading manually].

Actually, we can mix and match manual wrapping of overloaded functions and
automatic wrapping through [^BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS] and
its sister, [^BOOST_PYTHON_FUNCTION_OVERLOADS]. Following up on our example
presented in the section [link python.overloading on overloading], since the
first 4 overload functins have a common sequence of initial arguments, we
can use [^BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS] to automatically wrap the
first three of the [^def]s and manually wrap just the last. Here's
how we'll do this:

    BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(xf_overloads, f, 1, 4)

Create a member function pointers as above for both X::f overloads:

    bool    (X::*fx1)(int, double, char)    = &X::f;
    int     (X::*fx2)(int, int, int)        = &X::f;

Then...

    .def("f", fx1, xf_overloads());
    .def("f", fx2)

[endsect]
[endsect] [/ Functions ]

[section:object Object Interface]

Python is dynamically typed, unlike C++ which is statically typed. Python
variables may hold an integer, a float, list, dict, tuple, str, long etc.,
among other things. In the viewpoint of Boost.Python and C++, these
Pythonic variables are just instances of class [^object]. We will see in
this chapter how to deal with Python objects.

As mentioned, one of the goals of Boost.Python is to provide a
bidirectional mapping between C++ and Python while maintaining the Python
feel. Boost.Python C++ [^object]s are as close as possible to Python. This
should minimize the learning curve significantly.

[$images/python.png]

[section Basic Interface]

Class [^object] wraps [^PyObject*]. All the intricacies of dealing with
[^PyObject]s such as managing reference counting are handled by the
[^object] class. C++ object interoperability is seamless. Boost.Python C++
[^object]s can in fact be explicitly constructed from any C++ object.

To illustrate, this Python code snippet:

[python]

    def f(x, y):
         if (y == 'foo'):
             x[3:7] = 'bar'
         else:
             x.items += y(3, x)
         return x

    def getfunc():
       return f;

Can be rewritten in C++ using Boost.Python facilities this way:

[c++]

    object f(object x, object y) {
         if (y == "foo")
             x.slice(3,7) = "bar";
         else
             x.attr("items") += y(3, x);
         return x;
    }
    object getfunc() {
        return object(f);
    }

Apart from cosmetic differences due to the fact that we are writing the
code in C++, the look and feel should be immediately apparent to the Python
coder.

[endsect]
[section Derived Object types]

Boost.Python comes with a set of derived [^object] types corresponding to
that of Python's:

* list
* dict
* tuple
* str
* long_
* enum

These derived [^object] types act like real Python types. For instance:

    str(1) ==> "1"

Wherever appropriate, a particular derived [^object] has corresponding
Python type's methods. For instance, [^dict] has a [^keys()] method:

    d.keys()

[^make_tuple] is provided for declaring ['tuple literals]. Example:

    make_tuple(123, 'D', "Hello, World", 0.0);

In C++, when Boost.Python [^object]s are used as arguments to functions,
subtype matching is required. For example, when a function [^f], as
declared below, is wrapped, it will only accept instances of Python's
[^str] type and subtypes.

    void f(str name)
    {
        object n2 = name.attr("upper")();   // NAME = name.upper()
        str NAME = name.upper();            // better
        object msg = "%s is bigger than %s" % make_tuple(NAME,name);
    }

In finer detail:

    str NAME = name.upper();

Illustrates that we provide versions of the str type's methods as C++
member functions.

    object msg = "%s is bigger than %s" % make_tuple(NAME,name);

Demonstrates that you can write the C++ equivalent of [^"format" % x,y,z]
in Python, which is useful since there's no easy way to do that in std C++.

[blurb
    __alert__ [*Beware] the common pitfall of forgetting that the constructors
    of most of Python's mutable types make copies, just as in Python.
]

Python:
[python]

    >>> d = dict(x.__dict__)     # copies x.__dict__
    >>> d['whatever'] = 3        # modifies the copy