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Dean Moldovan67b52d82016-10-16 19:12:43 +02001Functions
2#########
3
4Before proceeding with this section, make sure that you are already familiar
5with the basics of binding functions and classes, as explained in :doc:`/basics`
6and :doc:`/classes`. The following guide is applicable to both free and member
7functions, i.e. *methods* in Python.
8
9Return value policies
10=====================
11
Wenzel Jakob6ba98652016-10-24 23:48:20 +020012Python and C++ use fundamentally different ways of managing the memory and
13lifetime of objects managed by them. This can lead to issues when creating
14bindings for functions that return a non-trivial type. Just by looking at the
15type information, it is not clear whether Python should take charge of the
16returned value and eventually free its resources, or if this is handled on the
17C++ side. For this reason, pybind11 provides a several `return value policy`
18annotations that can be passed to the :func:`module::def` and
19:func:`class_::def` functions. The default policy is
20:enum:`return_value_policy::automatic`.
Dean Moldovan67b52d82016-10-16 19:12:43 +020021
Wenzel Jakob6ba98652016-10-24 23:48:20 +020022Return value policies are tricky, and it's very important to get them right.
23Just to illustrate what can go wrong, consider the following simple example:
Dean Moldovan67b52d82016-10-16 19:12:43 +020024
25.. code-block:: cpp
26
Wenzel Jakob6ba98652016-10-24 23:48:20 +020027 /* Function declaration */
28 Data *get_data() { return _data; /* (pointer to a static data structure) */ }
29 ...
Dean Moldovan67b52d82016-10-16 19:12:43 +020030
Wenzel Jakob6ba98652016-10-24 23:48:20 +020031 /* Binding code */
32 m.def("get_data", &get_data); // <-- KABOOM, will cause crash when called from Python
33
34What's going on here? When ``get_data()`` is called from Python, the return
35value (a native C++ type) must be wrapped to turn it into a usable Python type.
36In this case, the default return value policy (:enum:`return_value_policy::automatic`)
37causes pybind11 to assume ownership of the static ``_data`` instance.
38
39When Python's garbage collector eventually deletes the Python
40wrapper, pybind11 will also attempt to delete the C++ instance (via ``operator
41delete()``) due to the implied ownership. At this point, the entire application
42will come crashing down, though errors could also be more subtle and involve
43silent data corruption.
44
45In the above example, the policy :enum:`return_value_policy::reference` should have
46been specified so that the global data instance is only *referenced* without any
47implied transfer of ownership, i.e.:
48
49.. code-block:: cpp
50
51 m.def("get_data", &get_data, return_value_policy::reference);
52
53On the other hand, this is not the right policy for many other situations,
54where ignoring ownership could lead to resource leaks.
55As a developer using pybind11, it's important to be familiar with the different
56return value policies, including which situation calls for which one of them.
57The following table provides an overview of available policies:
Dean Moldovan67b52d82016-10-16 19:12:43 +020058
59.. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}|
60
61+--------------------------------------------------+----------------------------------------------------------------------------+
62| Return value policy | Description |
63+==================================================+============================================================================+
Dean Moldovan67b52d82016-10-16 19:12:43 +020064| :enum:`return_value_policy::take_ownership` | Reference an existing object (i.e. do not create a new copy) and take |
65| | ownership. Python will call the destructor and delete operator when the |
66| | object's reference count reaches zero. Undefined behavior ensues when the |
Wenzel Jakob6ba98652016-10-24 23:48:20 +020067| | C++ side does the same, or when the data was not dynamically allocated. |
Dean Moldovan67b52d82016-10-16 19:12:43 +020068+--------------------------------------------------+----------------------------------------------------------------------------+
69| :enum:`return_value_policy::copy` | Create a new copy of the returned object, which will be owned by Python. |
70| | This policy is comparably safe because the lifetimes of the two instances |
71| | are decoupled. |
72+--------------------------------------------------+----------------------------------------------------------------------------+
73| :enum:`return_value_policy::move` | Use ``std::move`` to move the return value contents into a new instance |
74| | that will be owned by Python. This policy is comparably safe because the |
75| | lifetimes of the two instances (move source and destination) are decoupled.|
76+--------------------------------------------------+----------------------------------------------------------------------------+
77| :enum:`return_value_policy::reference` | Reference an existing object, but do not take ownership. The C++ side is |
78| | responsible for managing the object's lifetime and deallocating it when |
79| | it is no longer used. Warning: undefined behavior will ensue when the C++ |
80| | side deletes an object that is still referenced and used by Python. |
81+--------------------------------------------------+----------------------------------------------------------------------------+
82| :enum:`return_value_policy::reference_internal` | Indicates that the lifetime of the return value is tied to the lifetime |
83| | of a parent object, namely the implicit ``this``, or ``self`` argument of |
84| | the called method or property. Internally, this policy works just like |
85| | :enum:`return_value_policy::reference` but additionally applies a |
86| | ``keep_alive<0, 1>`` *call policy* (described in the next section) that |
87| | prevents the parent object from being garbage collected as long as the |
88| | return value is referenced by Python. This is the default policy for |
89| | property getters created via ``def_property``, ``def_readwrite``, etc. |
90+--------------------------------------------------+----------------------------------------------------------------------------+
Wenzel Jakob6ba98652016-10-24 23:48:20 +020091| :enum:`return_value_policy::automatic` | This is the default return value policy, which falls back to the policy |
92| | :enum:`return_value_policy::take_ownership` when the return value is a |
93| | pointer. Otherwise, it uses :enum:`return_value::move` or |
94| | :enum:`return_value::copy` for rvalue and lvalue references, respectively. |
95| | See above for a description of what all of these different policies do. |
96+--------------------------------------------------+----------------------------------------------------------------------------+
97| :enum:`return_value_policy::automatic_reference` | As above, but use policy :enum:`return_value_policy::reference` when the |
98| | return value is a pointer. This is the default conversion policy for |
99| | function arguments when calling Python functions manually from C++ code |
100| | (i.e. via handle::operator()). You probably won't need to use this. |
101+--------------------------------------------------+----------------------------------------------------------------------------+
102
Dean Moldovan03f627e2016-11-01 11:44:57 +0100103Return value policies can also be applied to properties:
Wenzel Jakob6ba98652016-10-24 23:48:20 +0200104
105.. code-block:: cpp
106
107 class_<MyClass>(m, "MyClass")
Dean Moldovan03f627e2016-11-01 11:44:57 +0100108 .def_property("data", &MyClass::getData, &MyClass::setData,
109 py::return_value_policy::copy);
110
111Technically, the code above applies the policy to both the getter and the
112setter function, however, the setter doesn't really care about *return*
113value policies which makes this a convenient terse syntax. Alternatively,
114targeted arguments can be passed through the :class:`cpp_function` constructor:
115
116.. code-block:: cpp
117
118 class_<MyClass>(m, "MyClass")
119 .def_property("data"
Wenzel Jakob6ba98652016-10-24 23:48:20 +0200120 py::cpp_function(&MyClass::getData, py::return_value_policy::copy),
121 py::cpp_function(&MyClass::setData)
122 );
Dean Moldovan67b52d82016-10-16 19:12:43 +0200123
124.. warning::
125
126 Code with invalid return value policies might access unitialized memory or
127 free data structures multiple times, which can lead to hard-to-debug
128 non-determinism and segmentation faults, hence it is worth spending the
129 time to understand all the different options in the table above.
130
Wenzel Jakob6ba98652016-10-24 23:48:20 +0200131.. note::
132
133 One important aspect of the above policies is that they only apply to
134 instances which pybind11 has *not* seen before, in which case the policy
135 clarifies essential questions about the return value's lifetime and
136 ownership. When pybind11 knows the instance already (as identified by its
137 type and address in memory), it will return the existing Python object
138 wrapper rather than creating a new copy.
Dean Moldovan67b52d82016-10-16 19:12:43 +0200139
140.. note::
141
142 The next section on :ref:`call_policies` discusses *call policies* that can be
143 specified *in addition* to a return value policy from the list above. Call
144 policies indicate reference relationships that can involve both return values
145 and parameters of functions.
146
147.. note::
148
149 As an alternative to elaborate call policies and lifetime management logic,
150 consider using smart pointers (see the section on :ref:`smart_pointers` for
151 details). Smart pointers can tell whether an object is still referenced from
152 C++ or Python, which generally eliminates the kinds of inconsistencies that
153 can lead to crashes or undefined behavior. For functions returning smart
154 pointers, it is not necessary to specify a return value policy.
155
156.. _call_policies:
157
158Additional call policies
159========================
160
161In addition to the above return value policies, further `call policies` can be
162specified to indicate dependencies between parameters. There is currently just
163one policy named ``keep_alive<Nurse, Patient>``, which indicates that the
164argument with index ``Patient`` should be kept alive at least until the
165argument with index ``Nurse`` is freed by the garbage collector. Argument
166indices start at one, while zero refers to the return value. For methods, index
167``1`` refers to the implicit ``this`` pointer, while regular arguments begin at
168index ``2``. Arbitrarily many call policies can be specified. When a ``Nurse``
169with value ``None`` is detected at runtime, the call policy does nothing.
170
171This feature internally relies on the ability to create a *weak reference* to
172the nurse object, which is permitted by all classes exposed via pybind11. When
173the nurse object does not support weak references, an exception will be thrown.
174
175Consider the following example: here, the binding code for a list append
176operation ties the lifetime of the newly added element to the underlying
177container:
178
179.. code-block:: cpp
180
181 py::class_<List>(m, "List")
182 .def("append", &List::append, py::keep_alive<1, 2>());
183
184.. note::
185
186 ``keep_alive`` is analogous to the ``with_custodian_and_ward`` (if Nurse,
187 Patient != 0) and ``with_custodian_and_ward_postcall`` (if Nurse/Patient ==
188 0) policies from Boost.Python.
189
190.. seealso::
191
192 The file :file:`tests/test_keep_alive.cpp` contains a complete example
193 that demonstrates using :class:`keep_alive` in more detail.
194
195.. _python_objects_as_args:
196
197Python objects as arguments
198===========================
199
200pybind11 exposes all major Python types using thin C++ wrapper classes. These
201wrapper classes can also be used as parameters of functions in bindings, which
202makes it possible to directly work with native Python types on the C++ side.
203For instance, the following statement iterates over a Python ``dict``:
204
205.. code-block:: cpp
206
207 void print_dict(py::dict dict) {
208 /* Easily interact with Python types */
209 for (auto item : dict)
210 std::cout << "key=" << item.first << ", "
211 << "value=" << item.second << std::endl;
212 }
213
214It can be exported:
215
216.. code-block:: cpp
217
218 m.def("print_dict", &print_dict);
219
220And used in Python as usual:
221
222.. code-block:: pycon
223
224 >>> print_dict({'foo': 123, 'bar': 'hello'})
225 key=foo, value=123
226 key=bar, value=hello
227
228For more information on using Python objects in C++, see :doc:`/advanced/pycpp/index`.
229
230Accepting \*args and \*\*kwargs
231===============================
232
233Python provides a useful mechanism to define functions that accept arbitrary
234numbers of arguments and keyword arguments:
235
236.. code-block:: python
237
238 def generic(*args, **kwargs):
239 ... # do something with args and kwargs
240
241Such functions can also be created using pybind11:
242
243.. code-block:: cpp
244
245 void generic(py::args args, py::kwargs kwargs) {
246 /// .. do something with args
247 if (kwargs)
248 /// .. do something with kwargs
249 }
250
251 /// Binding code
252 m.def("generic", &generic);
253
254The class ``py::args`` derives from ``py::tuple`` and ``py::kwargs`` derives
255from ``py::dict``. Note that the ``kwargs`` argument is invalid if no keyword
256arguments were actually provided. Please refer to the other examples for
257details on how to iterate over these, and on how to cast their entries into
258C++ objects. A demonstration is also available in
259``tests/test_kwargs_and_defaults.cpp``.
260
261.. warning::
262
263 Unlike Python, pybind11 does not allow combining normal parameters with the
264 ``args`` / ``kwargs`` special parameters.
265
266Default arguments revisited
267===========================
268
269The section on :ref:`default_args` previously discussed basic usage of default
270arguments using pybind11. One noteworthy aspect of their implementation is that
271default arguments are converted to Python objects right at declaration time.
272Consider the following example:
273
274.. code-block:: cpp
275
276 py::class_<MyClass>("MyClass")
277 .def("myFunction", py::arg("arg") = SomeType(123));
278
279In this case, pybind11 must already be set up to deal with values of the type
280``SomeType`` (via a prior instantiation of ``py::class_<SomeType>``), or an
281exception will be thrown.
282
283Another aspect worth highlighting is that the "preview" of the default argument
284in the function signature is generated using the object's ``__repr__`` method.
285If not available, the signature may not be very helpful, e.g.:
286
287.. code-block:: pycon
288
289 FUNCTIONS
290 ...
291 | myFunction(...)
292 | Signature : (MyClass, arg : SomeType = <SomeType object at 0x101b7b080>) -> NoneType
293 ...
294
295The first way of addressing this is by defining ``SomeType.__repr__``.
296Alternatively, it is possible to specify the human-readable preview of the
297default argument manually using the ``arg_v`` notation:
298
299.. code-block:: cpp
300
301 py::class_<MyClass>("MyClass")
302 .def("myFunction", py::arg_v("arg", SomeType(123), "SomeType(123)"));
303
304Sometimes it may be necessary to pass a null pointer value as a default
305argument. In this case, remember to cast it to the underlying type in question,
306like so:
307
308.. code-block:: cpp
309
310 py::class_<MyClass>("MyClass")
311 .def("myFunction", py::arg("arg") = (SomeType *) nullptr);