To deal with exceptions that hit destructors or other noexcept functions.
Includes fixes to support Python 2.7 and extends documentation on
error handling.
@virtuald and @YannickJadoul both contributed to this PR.
* Fix undefined memoryview format
* Add missing <algorithm> header
* Add workaround for py27 array compatibility
* Workaround py27 memoryview behavior
* Fix memoryview constructor from buffer_info
* Workaround PyMemoryView_FromMemory availability in py27
* Fix up memoryview tests
* Update memoryview test from buffer to check signedness
* Use static factory method to create memoryview
* Remove ndim arg from memoryview::frombuffer and add tests
* Allow ndim=0 memoryview and documentation fixup
* Use void* to align to frombuffer method signature
* Add const variants of frombuffer and frommemory
* Add memory view section in doc
* Fix docs
* Add test for null buffer
* Workaround py27 nullptr behavior in test
* Rename frombuffer to from_buffer
This adds support for a `py::args_kw_only()` annotation that can be
specified between `py::arg` annotations to indicate that any following
arguments are keyword-only. This allows you to write:
m.def("f", [](int a, int b) { /* ... */ },
py::arg("a"), py::args_kw_only(), py::arg("b"));
and have it work like Python 3's:
def f(a, *, b):
# ...
with respect to how `a` and `b` arguments are accepted (that is, `a` can
be positional or by keyword; `b` can only be specified by keyword).
* Adds std::deque to the types supported by list_caster in stl.h.
* Adds a new test_deque test in test_stl.{py,cpp}.
* Updates the documentation to include std::deque as a default
supported type.
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.
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.
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).
* 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]
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.
