155 lines
5.2 KiB
ReStructuredText
155 lines
5.2 KiB
ReStructuredText
STL containers
|
|
##############
|
|
|
|
Automatic conversion
|
|
====================
|
|
|
|
When including the additional header file :file:`pybind11/stl.h`, conversions
|
|
between ``std::vector<>``, ``std::list<>``, ``std::set<>``, and ``std::map<>``
|
|
and the Python ``list``, ``set`` and ``dict`` data structures are automatically
|
|
enabled. The types ``std::pair<>`` and ``std::tuple<>`` are already supported
|
|
out of the box with just the core :file:`pybind11/pybind11.h` header.
|
|
|
|
The major downside of these implicit conversions is that containers must be
|
|
converted (i.e. copied) on every Python->C++ and C++->Python transition, which
|
|
can have implications on the program semantics and performance. Please read the
|
|
next sections for more details and alternative approaches that avoid this.
|
|
|
|
.. note::
|
|
|
|
Arbitrary nesting of any of these types is possible.
|
|
|
|
.. seealso::
|
|
|
|
The file :file:`tests/test_python_types.cpp` contains a complete
|
|
example that demonstrates how to pass STL data types in more detail.
|
|
|
|
.. _opaque:
|
|
|
|
Making opaque types
|
|
===================
|
|
|
|
pybind11 heavily relies on a template matching mechanism to convert parameters
|
|
and return values that are constructed from STL data types such as vectors,
|
|
linked lists, hash tables, etc. This even works in a recursive manner, for
|
|
instance to deal with lists of hash maps of pairs of elementary and custom
|
|
types, etc.
|
|
|
|
However, a fundamental limitation of this approach is that internal conversions
|
|
between Python and C++ types involve a copy operation that prevents
|
|
pass-by-reference semantics. What does this mean?
|
|
|
|
Suppose we bind the following function
|
|
|
|
.. code-block:: cpp
|
|
|
|
void append_1(std::vector<int> &v) {
|
|
v.push_back(1);
|
|
}
|
|
|
|
and call it from Python, the following happens:
|
|
|
|
.. code-block:: pycon
|
|
|
|
>>> v = [5, 6]
|
|
>>> append_1(v)
|
|
>>> print(v)
|
|
[5, 6]
|
|
|
|
As you can see, when passing STL data structures by reference, modifications
|
|
are not propagated back the Python side. A similar situation arises when
|
|
exposing STL data structures using the ``def_readwrite`` or ``def_readonly``
|
|
functions:
|
|
|
|
.. code-block:: cpp
|
|
|
|
/* ... definition ... */
|
|
|
|
class MyClass {
|
|
std::vector<int> contents;
|
|
};
|
|
|
|
/* ... binding code ... */
|
|
|
|
py::class_<MyClass>(m, "MyClass")
|
|
.def(py::init<>)
|
|
.def_readwrite("contents", &MyClass::contents);
|
|
|
|
In this case, properties can be read and written in their entirety. However, an
|
|
``append`` operation involving such a list type has no effect:
|
|
|
|
.. code-block:: pycon
|
|
|
|
>>> m = MyClass()
|
|
>>> m.contents = [5, 6]
|
|
>>> print(m.contents)
|
|
[5, 6]
|
|
>>> m.contents.append(7)
|
|
>>> print(m.contents)
|
|
[5, 6]
|
|
|
|
Finally, the involved copy operations can be costly when dealing with very
|
|
large lists. To deal with all of the above situations, pybind11 provides a
|
|
macro named ``PYBIND11_MAKE_OPAQUE(T)`` that disables the template-based
|
|
conversion machinery of types, thus rendering them *opaque*. The contents of
|
|
opaque objects are never inspected or extracted, hence they *can* be passed by
|
|
reference. For instance, to turn ``std::vector<int>`` into an opaque type, add
|
|
the declaration
|
|
|
|
.. code-block:: cpp
|
|
|
|
PYBIND11_MAKE_OPAQUE(std::vector<int>);
|
|
|
|
before any binding code (e.g. invocations to ``class_::def()``, etc.). This
|
|
macro must be specified at the top level (and outside of any namespaces), since
|
|
it instantiates a partial template overload. If your binding code consists of
|
|
multiple compilation units, it must be present in every file preceding any
|
|
usage of ``std::vector<int>``. Opaque types must also have a corresponding
|
|
``class_`` declaration to associate them with a name in Python, and to define a
|
|
set of available operations, e.g.:
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::class_<std::vector<int>>(m, "IntVector")
|
|
.def(py::init<>())
|
|
.def("clear", &std::vector<int>::clear)
|
|
.def("pop_back", &std::vector<int>::pop_back)
|
|
.def("__len__", [](const std::vector<int> &v) { return v.size(); })
|
|
.def("__iter__", [](std::vector<int> &v) {
|
|
return py::make_iterator(v.begin(), v.end());
|
|
}, py::keep_alive<0, 1>()) /* Keep vector alive while iterator is used */
|
|
// ....
|
|
|
|
The ability to expose STL containers as native Python objects is a fairly
|
|
common request, hence pybind11 also provides an optional header file named
|
|
:file:`pybind11/stl_bind.h` that does exactly this. The mapped containers try
|
|
to match the behavior of their native Python counterparts as much as possible.
|
|
|
|
The following example showcases usage of :file:`pybind11/stl_bind.h`:
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Don't forget this
|
|
#include <pybind11/stl_bind.h>
|
|
|
|
PYBIND11_MAKE_OPAQUE(std::vector<int>);
|
|
PYBIND11_MAKE_OPAQUE(std::map<std::string, double>);
|
|
|
|
// ...
|
|
|
|
// later in binding code:
|
|
py::bind_vector<std::vector<int>>(m, "VectorInt");
|
|
py::bind_map<std::map<std::string, double>>(m, "MapStringDouble");
|
|
|
|
Please take a look at the :ref:`macro_notes` before using the
|
|
``PYBIND11_MAKE_OPAQUE`` macro.
|
|
|
|
.. seealso::
|
|
|
|
The file :file:`tests/test_opaque_types.cpp` contains a complete
|
|
example that demonstrates how to create and expose opaque types using
|
|
pybind11 in more detail.
|
|
|
|
The file :file:`tests/test_stl_binders.cpp` shows how to use the
|
|
convenience STL container wrappers.
|