A Python function can be called with the syntax:
```python
foo(a1, a2, *args, ka=1, kb=2, **kwargs)
```
This commit adds support for the equivalent syntax in C++:
```c++
foo(a1, a2, *args, "ka"_a=1, "kb"_a=2, **kwargs)
```
In addition, generalized unpacking is implemented, as per PEP 448,
which allows calls with multiple * and ** unpacking:
```python
bar(*args1, 99, *args2, 101, **kwargs1, kz=200, **kwargs2)
```
and
```c++
bar(*args1, 99, *args2, 101, **kwargs1, "kz"_a=200, **kwargs2)
```
Currently pybind11 only supports std::unique_ptr<T> holders by default
(other holders can, of course, be declared using the macro). PR #368
added a `py::nodelete` that is intended to be used as:
py::class_<Type, std::unique_ptr<Type, py::nodelete>> c("Type");
but this doesn't work out of the box. (You could add an explicit
holder type declaration, but this doesn't appear to have been the
intention of the commit).
This commit fixes it by generalizing the unique_ptr type_caster to take
both the type and deleter as template arguments, so that *any*
unique_ptr instances are now automatically handled by pybind. It also
adds a test to test_smart_ptr, testing both that py::nodelete (now)
works, and that the object is indeed not deleted as intended.
Problem
=======
The template trampoline pattern documented in PR #322 has a problem with
virtual method overloads in intermediate classes in the inheritance
chain between the trampoline class and the base class.
For example, consider the following inheritance structure, where `B` is
the actual class, `PyB<B>` is the trampoline class, and `PyA<B>` is an
intermediate class adding A's methods into the trampoline:
PyB<B> -> PyA<B> -> B -> A
Suppose PyA<B> has a method `some_method()` with a PYBIND11_OVERLOAD in
it to overload the virtual `A::some_method()`. If a Python class `C` is
defined that inherits from the pybind11-registered `B` and tries to
provide an overriding `some_method()`, the PYBIND11_OVERLOADs declared
in PyA<B> fails to find this overloaded method, and thus never invoke it
(or, if pure virtual and not overridden in PyB<B>, raises an exception).
This happens because the base (internal) `PYBIND11_OVERLOAD_INT` macro
simply calls `get_overload(this, name)`; `get_overload()` then uses the
inferred type of `this` to do a type lookup in `registered_types_cpp`.
This is where it fails: `this` will be a `PyA<B> *`, but `PyA<B>` is
neither the base type (`B`) nor the trampoline type (`PyB<B>`). As a
result, the overload fails and we get a failed overload lookup.
The fix
=======
The fix is relatively simple: we can cast `this` passed to
`get_overload()` to a `const B *`, which lets get_overload look up the
correct class. Since trampoline classes should be derived from `B`
classes anyway, this cast should be perfectly safe.
This does require adding the class name as an argument to the
PYBIND11_OVERLOAD_INT macro, but leaves the public macro signatures
unchanged.
- ICPC can't handle the NCVirt trampoline which returns a non-copyable
type, which is likely due to a constexpr/SFINAE issue. This disables
the test on that compiler so that at least the rest can be tested.
For example keep_alive<0,1>() should work where the return value may sometimes be None. At present a "Could not allocate weak reference!" exception is thrown.
Update documentation to clarify behaviour of keep_alive when nurse is None or does not support weak references.
This is required since format descriptors for string types that
were using PYBIND11_DESCR were causing problems on C++14 on Linux.
Although this is technically a breaking change, it shouldn't cause
problems since the only use of format strings is passing them to
buffer_info constructor which expects std::string.
Note: for non-structured types, the const char * value is still
accessible via ::value for compatibility purpose.
The format strings that are known at compile time are now accessible
via both ::value and ::format(), and format strings for everything
else is accessible via ::format(). This makes it backwards compatible.
This allows exposing a dict-like interface to python code, allowing
iteration over keys via:
for k in custommapping:
...
while still allowing iteration over pairs, so that you can also
implement 'dict.items()' functionality which returns a pair iterator,
allowing:
for k, v in custommapping.items():
...
example-sequences-and-iterators is updated with a custom class providing
both types of iteration.
