...one of the most highly
regarded and expertly designed C++ library projects in the
world.
— Herb Sutter and Andrei
Alexandrescu, C++
Coding Standards
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.
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:
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:
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.
Boost.Python comes with a set of derived object
types
corresponding to that of Python's:
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++.
Python:
>>> d = dict(x.__dict__) # copies x.__dict__ >>> d['whatever'] = 3 # modifies the copy
C++:
dict d(x.attr("__dict__")); // copies x.__dict__ d['whatever'] = 3; // modifies the copy
Due to the dynamic nature of Boost.Python objects, any class_<T>
may also be one of these types! The following code snippet wraps the class
(type) object.
We can use this to create wrapped instances. Example:
object vec345 = ( class_<Vec2>("Vec2", init<double, double>()) .def_readonly("length", &Point::length) .def_readonly("angle", &Point::angle) )(3.0, 4.0); assert(vec345.attr("length") == 5.0);
At some point, we will need to get C++ values out of object instances. This
can be achieved with the extract<T>
function. Consider
the following:
double x = o.attr("length"); // compile error
In the code above, we got a compiler error because Boost.Python object
can't be implicitly converted to double
s. Instead, what
we wanted to do above can be achieved by writing:
double l = extract<double>(o.attr("length")); Vec2& v = extract<Vec2&>(o); assert(l == v.length());
The first line attempts to extract the "length" attribute of the
Boost.Python object
. The second line attempts to extract
the Vec2
object from held by the Boost.Python object
.
Take note that we said "attempt to" above. What if the Boost.Python
object
does not really hold a Vec2
type? This is certainly a possibility considering the dynamic nature of Python
object
s. To be on the safe side, if the C++ type can't
be extracted, an appropriate exception is thrown. To avoid an exception,
we need to test for extractibility:
extract<Vec2&> x(o); if (x.check()) { Vec2& v = x(); ...
The astute reader might have noticed that the
extract<T>
facility in fact solves the mutable copying problem:
dict d = extract<dict>(x.attr("__dict__")); d["whatever"] = 3; // modifies x.__dict__ !
Boost.Python has a nifty facility to capture and wrap C++ enums. While Python
has no enum
type, we'll often want to expose our C++ enums
to Python as an int
. Boost.Python's enum facility makes
this easy while taking care of the proper conversions from Python's dynamic
typing to C++'s strong static typing (in C++, ints cannot be implicitly converted
to enums). To illustrate, given a C++ enum:
enum choice { red, blue };
the construct:
enum_<choice>("choice") .value("red", red) .value("blue", blue) ;
can be used to expose to Python. The new enum type is created in the current
scope()
, which is usually the current module. The snippet
above creates a Python class derived from Python's int
type which is associated with the C++ type passed as its first parameter.
![]() |
Note |
---|---|
what is a scope? The scope is a class that has an associated global Python object which controls the Python namespace in which new extension classes and wrapped functions will be defined as attributes. Details can be found here. |
You can access those values in Python as
>>> my_module.choice.red my_module.choice.red
where my_module is the module where the enum is declared. You can also create a new scope around a class:
scope in_X = class_<X>("X") .def( ... ) .def( ... ) ; // Expose X::nested as X.nested enum_<X::nested>("nested") .value("red", red) .value("blue", blue) ;
When you want a boost::python::object
to manage a pointer to PyObject*
pyobj one does:
boost::python::object o(boost::python::handle<>(pyobj));
In this case, the o
object,
manages the pyobj
, it won’t
increase the reference count on construction.
Otherwise, to use a borrowed reference:
boost::python::object o(boost::python::handle<>(boost::python::borrowed(pyobj)));
In this case, Py_INCREF
is
called, so pyobj
is not destructed
when object o goes out of scope.