This PR adds a new py::ellipsis() method which can be used in
conjunction with NumPy's generalized slicing support. For instance,
the following is now valid (where "a" is a NumPy array):
py::array b = a[py::make_tuple(0, py::ellipsis(), 0)];
* Add basic support for tag-based static polymorphism
Sometimes it is possible to look at a C++ object and know what its dynamic type is,
even if it doesn't use C++ polymorphism, because instances of the object and its
subclasses conform to some other mechanism for being self-describing; for example,
perhaps there's an enumerated "tag" or "kind" member in the base class that's always
set to an indication of the correct type. This might be done for performance reasons,
or to permit most-derived types to be trivially copyable. One of the most widely-known
examples is in LLVM: https://llvm.org/docs/HowToSetUpLLVMStyleRTTI.html
This PR permits pybind11 to be informed of such conventions via a new specializable
detail::polymorphic_type_hook<> template, which generalizes the previous logic for
determining the runtime type of an object based on C++ RTTI. Implementors provide
a way to map from a base class object to a const std::type_info* for the dynamic
type; pybind11 then uses this to ensure that casting a Base* to Python creates a
Python object that knows it's wrapping the appropriate sort of Derived.
There are a number of restrictions with this tag-based static polymorphism support
compared to pybind11's existing support for built-in C++ polymorphism:
- there is no support for this-pointer adjustment, so only single inheritance is permitted
- there is no way to make C++ code call new Python-provided subclasses
- when binding C++ classes that redefine a method in a subclass, the .def() must be
repeated in the binding for Python to know about the update
But these are not much of an issue in practice in many cases, the impact on the
complexity of pybind11's innards is minimal and localized, and the support for
automatic downcasting improves usability a great deal.
The property returns the enum_ value as a string.
For example:
>>> import module
>>> module.enum.VALUE
enum.VALUE
>>> str(module.enum.VALUE)
'enum.VALUE'
>>> module.enum.VALUE.name
'VALUE'
This is actually the equivalent of Boost.Python "name" property.
I think that there's the word "for" missing for that sentence to be correct.
Please double-check that the sentence means what it's supposed to mean. :-)
- PYBIND11_MAKE_OPAQUE now takes ... rather than a single argument and
expands it with __VA_ARGS__; this lets templated, comma-containing
types get through correctly.
- Adds a new macro PYBIND11_TYPE() that lets you pass the type into a
macro as a single argument, such as:
PYBIND11_OVERLOAD(PYBIND11_TYPE(R<1,2>), PYBIND11_TYPE(C<3,4>), func)
Unfortunately this only works for one macro call: to forward the
argument on to the next macro call (without the processor breaking it
up again) requires also adding the PYBIND11_TYPE(...) to type macro
arguments in the PYBIND11_OVERLOAD_... macro chain.
- updated the documentation with these two changes, and use them at a couple
places in the test suite to test that they work.
None of the three currently recommended approaches works on PyPy, due to
it not garbage collecting things when you want it to. Added a note with
example showing how to get interpreter shutdown callbacks using the Python
atexit module.
py::class_<T>'s `def_property` and `def_property_static` can now take a
`nullptr` as the getter to allow a write-only property to be established
(mirroring Python's `property()` built-in when `None` is given for the
getter).
This also updates properties to use the new nullptr constructor internally.
This also matches the Eigen example for the row-major case.
This also enhances one of the tests to trigger a failure (and fixes it in the PR). (This isn't really a flaw in pybind itself, but rather fixes wrong code in the test code and docs).
MSCV does not allow `&typeid(T)` in constexpr contexts, but the string
part of the type signature can still be constexpr. In order to avoid
`typeid` as long as possible, `descr` is modified to collect type
information as template parameters instead of constexpr `typeid`.
The actual `std::type_info` pointers are only collected in the end,
as a `constexpr` (gcc/clang) or regular (MSVC) function call.
Not only does it significantly reduce binary size on MSVC, gcc/clang
benefit a little bit as well, since they can skip some intermediate
`std::type_info*` arrays.
* Expand documentation to include explicit example of py::module::import
where one would expect it.
* Describe how to use unbound and bound methods to class Python classes.
[skip ci]
E.g. trying to convert a `list` to a `std::vector<int>` without
including <pybind11/stl.h> will now raise an error with a note that
suggests checking the headers.
The note is only appended if `std::` is found in the function
signature. This should only be the case when a header is missing.
E.g. when stl.h is included, the signature would contain `List[int]`
instead of `std::vector<int>` while using stl_bind.h would produce
something like `MyVector`. Similarly for `std::map`/`Dict`, `complex`,
`std::function`/`Callable`, etc.
There's a possibility for false positives, but it's pretty low.
To avoid an ODR violation in the test suite while testing
both `stl.h` and `std_bind.h` with `std::vector<bool>`,
the `py::bind_vector<std::vector<bool>>` test is moved to
the secondary module (which does not include `stl.h`).
PR #880 changed the implementation of keep_alive to avoid weak
references when the nurse is pybind11-registered, but the documentation
didn't get updated to match.
There are two separate additions:
1. `py::hash(obj)` is equivalent to the Python `hash(obj)`.
2. `.def(hash(py::self))` registers the hash function defined by
`std::hash<T>` as the Python hash function.
