Python 3's `PyInstanceMethod_Type` hides itself via its `tp_descr_get`,
which prevents aliasing methods via `cls.attr("m2") = cls.attr("m1")`:
instead the `tp_descr_get` returns a plain function, when called on a
class, or a `PyMethod`, when called on an instance. Override that
behaviour for pybind11 types with a special bypass for
`PyInstanceMethod_Types`.
The Unicode support added in 2.1 (PR #624) inadvertently broke accepting
`bytes` as std::string/char* arguments. This restores it with a
separate path that does a plain conversion (i.e. completely bypassing
all the encoding/decoding code), but only for single-byte string types.
The numpy API constants can check past the end of the API array if the
numpy version is too old thus causing a segfault. The current list of
functions requires numpy >= 1.7.0, so this adds a check and exception if
numpy is too old.
The added feature version API element was added in numpy 1.4.0, so this
could still segfault if loaded in 1.3.0 or earlier, but given that
1.4.0 was released at the end of 2009, it seems reasonable enough to
not worry about that case. (1.7.0 was released in early 2013).
This commits adds base class pointers of offset base classes (i.e. due
to multiple inheritance) to `registered_instances` so that if such a
pointer is returned we properly recognize it as an existing instance.
Without this, returning a base class pointer will cast to the existing
instance if the pointer happens to coincide with the instance pointer,
but constructs a new instance (quite possibly with a segfault, if
ownership is applied) for unequal base class pointers due to multiple
inheritance.
When we are returned a base class pointer (either directly or via
shared_from_this()) we detect its runtime type (using `typeid`), then
end up essentially reinterpret_casting the pointer to the derived type.
This is invalid when the base class pointer was a non-first base, and we
end up with an invalid pointer. We could dynamic_cast to the
most-derived type, but if *that* type isn't pybind11-registered, the
resulting pointer given to the base `cast` implementation isn't necessarily valid
to be reinterpret_cast'ed back to the backup type.
This commit removes the "backup" type argument from the many-argument
`cast(...)` and instead does the derived-or-pointer type decision and
type lookup in type_caster_base, where the dynamic_cast has to be to
correctly get the derived pointer, but also has to do the type lookup to
ensure that we don't pass the wrong (derived) pointer when the backup
type (i.e. the type caster intrinsic type) pointer is needed.
Since the lookup is needed before calling the base cast(), this also
changes the input type to a detail::type_info rather than doing a
(second) lookup in cast().
This breaks up the instance management functions in class_support.h a
little bit so that other pybind11 code can use it. In particular:
- added make_new_instance() which does what pybind11_object_new does,
but also allows instance allocation without `value` allocation. This
lets `cast.h` use the same instance allocation rather than having its
own separate implementation.
- instance registration is now moved to a
`register_instance()`/deregister_instance()` pair (rather than having
individual code add or remove things from `registered_instances`
directory).
- clear_instance() does everything `pybind11_object_dealloc()` needs
except for the deallocation; this is helpful for factory construction
which needs to be able to replace the internals of an instance without
deallocating it.
- clear_instance() now also calls `dealloc` when `holder_constructed`
is true, even if `value` is false. This can happen in factory
construction when the pointer is moved from one instance to another,
but the holder itself is only copied (i.e. for a shared_ptr holder).
I got some unexpected errors from code using `overload_cast` until I
realized that I'd configured the build with -std=c++11.
This commit adds a fake `overload_cast` class in C++11 mode that
triggers a static_assert failure indicating that C++14 is needed.
We currently fail at runtime when trying to call a method that is
overloaded with both static and non-static methods. This is something
python won't allow: the object is either a function or an instance, and
can't be both.
This further reduces the constructors required in buffer_info/numpy by
removing the need for the constructors that take a single size_t and
just forward it on via an initializer_list to the container-accepting
constructor.
Unfortunately, in `array` one of the constructors runs into an ambiguity
problem with the deprecated `array(handle, bool)` constructor (because
both the bool constructor and the any_container constructor involve an
implicit conversion, so neither has precedence), so a forwarding
constructor is kept there (until the deprecated constructor is
eventually removed).
This adds support for constructing `buffer_info` and `array`s using
arbitrary containers or iterator pairs instead of requiring a vector.
This is primarily needed by PR #782 (which makes strides signed to
properly support negative strides, and will likely also make shape and
itemsize to avoid mixed integer issues), but also needs to preserve
backwards compatibility with 2.1 and earlier which accepts the strides
parameter as a vector of size_t's.
Rather than adding nearly duplicate constructors for each stride-taking
constructor, it seems nicer to simply allow any type of container (or
iterator pairs). This works by replacing the existing vector arguments
with a new `detail::any_container` class that handles implicit
conversion of arbitrary containers into a vector of the desired type.
It can also be explicitly instantiated with a pair of iterators (e.g.
by passing {begin, end} instead of the container).
Upcoming changes to buffer_info make it need some things declared in
common.h; it also feels a bit misplaced in common.h (which is arguably
too large already), so move it out. (Separating this and the subsequent
changes into separate commits to make the changes easier to distinguish
from the move.)
When attempting to get a raw array pointer we return nullptr if given a
nullptr, which triggers an error_already_set(), but we haven't set an
exception message, which results in "Unknown internal error".
Callers that want explicit allowing of a nullptr here already handle it
(by clearing the exception after the call).
Many of the Eigen type casters' name() methods weren't wrapping the type
description in a `type_descr` object, which thus wasn't adding the
"{...}" annotation used to identify an argument which broke the help
output by skipping eigen arguments.
The test code I had added even had some (unnoticed) broken output (with
the "arg0: " showing up in the return value).
This commit also adds test code to ensure that named eigen arguments
actually work properly, despite the invalid help output. (The added
tests pass without the rest of this commit).
The holder casters assume but don't check that a `holder<type>`'s `type`
is really a `type_caster_base<type>`; this adds a static_assert to make
sure this is really the case, to turn things like
`std::shared_ptr<array>` into a compilation failure.
Fixes#785
Fixes#775.
Assignments of the form `Type.static_prop = value` should be translated to
`Type.static_prop.__set__(value)` except when `isinstance(value, static_prop)`.
PR #771 deprecated them as they can cause linking failures (#770), but
the deprecation tags cause warnings on GCC 5.x through 6.2.x. Removing
them entirely will break backwards-compatibility consequences, but the
effects should be minimal (only code that was inheriting from `object`
could get at them at all as they are protected).
Fixes#777
When make_tuple fails (for example, when print() is called with a
non-convertible argument, as in #778) the error message a less helpful
than it could be:
make_tuple(): unable to convert arguments of types 'std::tuple<type1, type2>' to Python object
There is no actual std::tuple involved (only a parameter pack and a
Python tuple), but it also doesn't immediately reveal which type caused
the problem.
This commit changes the debugging mode output to show just the
problematic type:
make_tuple(): unable to convert argument of type 'type2' to Python object
This commit adds `error_already_set::matches()` convenience method to
check if the exception trapped by `error_already_set` matches a given
Python exception type. This will address #700 by providing a less
verbose way to check exceptions.
The constexpr static instances can cause linking failures if the
compiler doesn't optimize away the reference, as reported in #770.
There's no particularly nice way of fixing this in C++11/14: we can't
inline definitions to match the declaration aren't permitted for
non-templated static variables (C++17 *does* allows "inline" on
variables, but that obviously doesn't help us.)
One solution that could work around it is to add an extra inherited
subclass to `object`'s hierarchy, but that's a bit of a messy solution
and was decided against in #771 in favour of just deprecating (and
eventually dropping) the constexpr statics.
Fixes#770.
The extends the previous unchecked support with the ability to
determine the dimensions at runtime. This incurs a small performance
hit when used (versus the compile-time fixed alternative), but is still considerably
faster than the full checks on every call that happen with
`.at()`/`.mutable_at()`.
This adds bounds-unchecked access to arrays through a `a.unchecked<Type,
Dimensions>()` method. (For `array_t<T>`, the `Type` template parameter
is omitted). The mutable version (which requires the array have the
`writeable` flag) is available as `a.mutable_unchecked<...>()`.
Specifying the Dimensions as a template parameter allows storage of an
std::array; having the strides and sizes stored that way (as opposed to
storing a copy of the array's strides/shape pointers) allows the
compiler to make significant optimizations of the shape() method that it
can't make with a pointer; testing with nested loops of the form:
for (size_t i0 = 0; i0 < r.shape(0); i0++)
for (size_t i1 = 0; i1 < r.shape(1); i1++)
...
r(i0, i1, ...) += 1;
over a 10 million element array gives around a 25% speedup (versus using
a pointer) for the 1D case, 33% for 2D, and runs more than twice as fast
with a 5D array.
This extends the trivial handling to support trivial handling for
Fortran-order arrays (i.e. column major): if inputs aren't all
C-contiguous, but *are* all F-contiguous, the resulting array will be
F-contiguous and we can do trivial processing.
For anything else (e.g. C-contiguous, or inputs requiring non-trivial
processing), the result is in (numpy-default) C-contiguous layout.
The only part of the vectorize code that actually needs c-contiguous is
the "trivial" broadcast; for non-trivial arguments, the code already
uses strides properly (and so handles C-style, F-style, neither, slices,
etc.)
This commit rewrites `broadcast` to additionally check for C-contiguous
storage, then takes off the `c_style` flag for the arguments, which
will keep the functionality more or less the same, except for no longer
requiring an array copy for non-c-contiguous input arrays.
Additionally, if we're given a singleton slice (e.g. a[0::4, 0::4] for a
4x4 or smaller array), we no longer fail triviality because the trivial
code path never actually uses the strides on a singleton.
Instead of a segfault. Fixes#751.
This covers the case of loading a custom holder from a default-holder
instance. Attempting to load one custom holder from a different custom
holder (i.e. not `std::unique_ptr`) yields undefined behavior, just as
#588 established for inheritance.
py::arg() doesn't only specify named arguments anymore, so the error
message was misleading (e.g. when using `py::arg().noconvert()` and
forgetting `py::arg()` for a second positional argument).
We now require (and enforce at compile time):
- GCC 4.8+
- clang 3.3+ (5.0+ for Apple's renumbered clang)
- MSVC 2015u3+
- ICC 15+
This also updates the versions listed in the README, and removes a
now-redundant MSVC version check.
This adds brief API documentation for make_iterator/make_key_iterator,
specifically mentioning that it requires InputIterators.
Closes#734.
[skip ci] (no code change here)
We can't support this for classes from imported modules (which is the
primary purpose of a ctor argument base class) because we *have* to
have both parent and derived to properly extract a multiple-inheritance
base class pointer from a derived class pointer.
We could support this for actual `class_<Base, ...> instances, but since
in that case the `Base` is already present in the code, it seems more
consistent to simply always require MI to go via template options.
This puts the fold expressions behind the feature macro instead of a
general C++17 macro.
It also adds a fold expression optimization to constexpr_sum (guarded
by the same feature macro).
Fixes#738
The current check for conformability fails when given a 2D, 1xN or Nx1
input to a row-major or column-major, respectively, Eigen::Ref, leading
to a copy-required state in the type_caster, but this later failed
because the copy was also non-conformable because it had the same shape
and strides (because a 1xN or Nx1 is both F and C contiguous).
In such cases we can safely ignore the stride on the "1" dimension since
it'll never be used: only the "N" dimension stride needs to match the
Eigen::Ref stride, which both fixes the non-conformable copy problem,
but also avoids a copy entirely as long as the "N" dimension has a
compatible stride.
Allows use of vectors as python buffers, so for example they can be adopted without a copy by numpy.asarray
Allows faster conversion of buffers to vectors by copying instead of individually casting the elements
* Add value_type member alias to py::array_t (resolve#632)
* Use numpy scalar name in py::array_t function signatures (e.g. float32/64 instead of just float)
