* Change NAMESPACE_BEGIN and NAMESPACE_END macros into PYBIND11_NAMESPACE_BEGIN and PYBIND11_NAMESPACE_END
* Fix sudden HomeBrew 'python not installed' error
* Sweep difference in 'Class.__init__() must be called when overriding __init__' error message between CPython and PyPy under the rug
* Homebrew updated to 3.8 yesterday.
Co-authored-by: Henry Schreiner <HenrySchreinerIII@gmail.com>
* stl.h: propagate return value policies to type-specific casters
Return value policies for containers like those handled in in 'stl.h'
are currently broken.
The problem is that detail::return_value_policy_override<C>::policy()
always returns 'move' when given a non-pointer/reference type, e.g.
'std::vector<...>'.
This is sensible behavior for custom types that are exposed via
'py::class_<>', but it does not make sense for types that are handled by
other type casters (STL containers, Eigen matrices, etc.).
This commit changes the behavior so that
detail::return_value_policy_override only becomes active when the type
caster derives from type_caster_generic.
Furthermore, the override logic is called recursively in STL type
casters to enable key/value-specific behavior.
In the latest MSVC in C++17 mode including Eigen causes warnings:
warning C4996: 'std::unary_negate<_Fn>': warning STL4008: std::not1(),
std::not2(), std::unary_negate, and std::binary_negate are deprecated in
C++17. They are superseded by std::not_fn(). You can define
_SILENCE_CXX17_NEGATORS_DEPRECATION_WARNING or
_SILENCE_ALL_CXX17_DEPRECATION_WARNINGS to acknowledge that you have
received this warning.
This disables 4996 for the Eigen includes.
Catch generates a similar warning for std::uncaught_exception, so
disable the warning there, too.
In both cases this is temporary; we can (and should) remove the warnings
disabling once new upstream versions of Eigen and Catch are available
that address the warning. (The Catch one, in particular, looks to be
fixed in upstream master, so will probably be fixed in the next (2.0.2)
release).
This commit turns on `-Wdeprecated` in the test suite and fixes several
associated deprecation warnings that show up as a result:
- in C++17 `static constexpr` members are implicitly inline; our
redeclaration (needed for C++11/14) is deprecated in C++17.
- various test suite classes have destructors and rely on implicit copy
constructors, but implicit copy constructor definitions when a
user-declared destructor is present was deprecated in C++11.
- Eigen also has various implicit copy constructors, so just disable
`-Wdeprecated` in `eigen.h`.
This fixes a bug introduced in b68959e822
when passing in a two-dimensional, but conformable, array as the value
for a compile-time Eigen vector (such as VectorXd or RowVectorXd). The
commit switched to using numpy to copy into the eigen data, but this
broke the described case because numpy refuses to broadcast a (N,1)
into a (N).
This commit fixes it by squeezing the input array whenever the output
array is 1-dimensional, which will let the problematic case through.
(This shouldn't squeeze inappropriately as dimension compatibility is
already checked for conformability before getting to the copy code).
`type_descr` is now applied only to the final signature so that it only
marks the argument types, but not nested types (e.g. for tuples) or
return types.
The current C++14 constexpr signatures don't require relaxed constexpr,
but only `auto` return type deduction. To get around this in C++11,
the type caster's `name()` static member functions are turned into
`static constexpr auto` variables.
This adds a PYBIND11_NAMESPACE macro that expands to the `pybind11`
namespace with hidden visibility under gcc-type compilers, and otherwise
to the plain `pybind11`. This then forces hidden visibility on
everything in pybind, solving the visibility issues discussed at end
end of #949.
This commit allows type_casters to allow their local values to be moved
away, rather than copied, when the type caster instance itself is an rvalue.
This only applies (automatically) to type casters using
PYBIND11_TYPE_CASTER; the generic type type casters don't own their own
pointer, and various value casters (e.g. std::string, std::pair,
arithmetic types) already cast to an rvalue (i.e. they return by value).
This updates various calling code to attempt to get a movable value
whenever the value is itself coming from a type caster about to be
destroyed: for example, when constructing an std::pair or various stl.h
containers. For types that don't support value moving, the cast_op
falls back to an lvalue cast.
There wasn't an obvious place to add the tests, so I added them to
test_copy_move_policies, but also renamed it to drop the _policies as it
now tests more than just policies.
We're current copy by creating an Eigen::Map into the input numpy
array, then assigning that to the basic eigen type, effectively having
Eigen do the copy. That doesn't work for negative strides, though:
Eigen doesn't allow them.
This commit makes numpy do the copying instead by allocating the eigen
type, then having numpy copy from the input array into a numpy reference
into the eigen object's data. This also saves a copy when type
conversion is required: numpy can do the conversion on-the-fly as part
of the copy.
Finally this commit also makes non-reference parameters respect the
convert flag, declining the load when called in a noconvert pass with a
convertible, but non-array input or an array with the wrong dtype.
`EigenConformable::stride_compatible` returns false if the strides are
negative. In this case, do not use `EigenConformable::stride`, as it
is {0,0}. We cannot write negative strides in this element, as Eigen
will throw an assertion if we do.
The `type_caster` specialization for regular, dense Eigen matrices now
does a second `array_t::ensure` to copy data in case of negative strides.
I'm not sure that this is the best way to implement this.
I have added "TODO" tags linking these changes to Eigen bug #747, which,
when fixed, will allow Eigen to accept negative strides.
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).
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).
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.
This commit largely rewrites the Eigen dense matrix support to avoid
copying in many cases: Eigen arguments can now reference numpy data, and
numpy objects can now reference Eigen data (given compatible types).
Eigen::Ref<...> arguments now also make use of the new `convert`
argument use (added in PR #634) to avoid conversion, allowing
`py::arg().noconvert()` to be used when binding a function to prohibit
copying when invoking the function. Respecting `convert` also means
Eigen overloads that avoid copying will be preferred during overload
resolution to ones that require copying.
This commit also rewrites the Eigen documentation and test suite to
explain and test the new capabilities.
Currently when we do a conversion between a numpy array and an Eigen
Vector, we allow the conversion only if the Eigen type is a
compile-time vector (i.e. at least one dimension is fixed at 1 at
compile time), or if the type is dynamic on *both* dimensions.
This means we can run into cases where MatrixXd allow things that
conforming, compile-time sizes does not: for example,
`Matrix<double,4,Dynamic>` is currently not allowed, even when assigning
from a 4-element vector, but it *is* allowed for a
`Matrix<double,Dynamic,Dynamic>`.
This commit also reverts the current behaviour of using the matrix's
storage order to determine the structure when the Matrix is fully
dynamic (i.e. in both dimensions). Currently we assign to an eigen row
if the storage order is row-major, and column otherwise: this seems
wrong (the storage order has nothing to do with the shape!). While
numpy doesn't distinguish between a row/column vector, Eigen does, but
it makes more sense to consistently choose one than to produce
something with a different shape based on the intended storage layout.
This replaces the current `all_of_t<Pred, Ts...>` with `all_of<Ts...>`,
with previous use of `all_of_t<Pred, Ts...>` becoming
`all_of<Pred<Ts>...>` (and similarly for `any_of_t`). It also adds a
`none_of<Ts...>`, a shortcut for `negation<any_of<Ts...>>`.
This allows `all_of` and `any_of` to be used a bit more flexible, e.g.
in cases where several predicates need to be tested for the same type
instead of the same predicate for multiple types.
This commit replaces the implementation with a more efficient version
for non-MSVC. For MSVC, this changes the workaround to use the
built-in, recursive std::conjunction/std::disjunction instead.
This also removes the `count_t` since `any_of_t` and `all_of_t` were the
only things using it.
This commit also rearranges some of the future std imports to use actual
`std` implementations for C++14/17 features when under the appropriate
compiler mode, as we were already doing for a few things (like
index_sequence). Most of these aren't saving much (the implementation
for enable_if_t, for example, is trivial), but I think it makes the
intention of the code instantly clear. It also enables MSVC's native
std::index_sequence support.
* `array_t(const object &)` now throws on error
* `array_t::ensure()` is intended for casters —- old constructor is
deprecated
* `array` and `array_t` get default constructors (empty array)
* `array` gets a converting constructor
* `py::isinstance<array_T<T>>()` checks the type (but not flags)
There is only one special thing which must remain: `array_t` gets
its own `type_caster` specialization which uses `ensure` instead
of a simple check.
The pytype converting constructors are convenient and safe for user
code, but for library internals the additional type checks and possible
conversions are sometimes not desired. `reinterpret_borrow<T>()` and
`reinterpret_steal<T>()` serve as the low-level unsafe counterparts
of `cast<T>()`.
This deprecates the `object(handle, bool)` constructor.
Renamed `borrowed` parameter to `is_borrowed` to avoid shadowing
warnings on MSVC.
Allows checking the Python types before creating an object instead of
after. For example:
```c++
auto l = list(ptr, true);
if (l.check())
// ...
```
The above is replaced with:
```c++
if (isinstance<list>(ptr)) {
auto l = reinterpret_borrow(ptr);
// ...
}
```
This deprecates `py::object::check()`. `py::isinstance()` covers the
same use case, but it can also check for user-defined types:
```c++
class Pet { ... };
py::class_<Pet>(...);
m.def("is_pet", [](py::object obj) {
return py::isinstance<Pet>(obj); // works as expected
});
```
This clears the Python error at the error_already_set throw site, thus
allowing Python calls to be made in destructors which are triggered by
the exception. This is preferable to the alternative, which would be
guarding every Python API call with an error_scope.
This effectively flips the behavior of error_already_set. Previously,
it was assumed that the error stays in Python, so handling the exception
in C++ would require explicitly calling PyErr_Clear(), but nothing was
needed to propagate the error to Python. With this change, handling the
error in C++ does not require a PyErr_Clear() call, but propagating the
error to Python requires an explicit error_already_set::restore().
The change does not break old code which explicitly calls PyErr_Clear()
for cleanup, which should be the majority of user code. The need for an
explicit restore() call does break old code, but this should be mostly
confined to the library and not user code.
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.
Functions returning specialized Eigen matrices like Eigen::DiagonalMatrix and
Eigen::SelfAdjointView--which inherit from EigenBase but not
DenseBase--isn't currently allowed; such classes are explicitly copyable
into a Matrix (by definition), and so we can support functions that
return them by copying the value into a Matrix then casting that
resulting dense Matrix into a numpy.ndarray. This commit does exactly
that.
Some Eigen objects, such as those returned by matrix.diagonal() and
matrix.block() have non-standard stride values because they are
basically just maps onto the underlying matrix without copying it (for
example, the primary diagonal of a 3x3 matrix is a vector-like object
with .src equal to the full matrix data, but with stride 4). Returning
such an object from a pybind11 method breaks, however, because pybind11
assumes vectors have stride 1, and that matrices have strides equal to
the number of rows/columns or 1 (depending on whether the matrix is
stored column-major or row-major).
This commit fixes the issue by making pybind11 use Eigen's stride
methods when copying the data.
Eigen::Ref is a common way to pass eigen dense types without needing a
template, e.g. the single definition `void
func(Eigen::Ref<Eigen::MatrixXd> x)` can be called with any double
matrix-like object.
The current pybind11 eigen support fails with internal errors if
attempting to bind a function with an Eigen::Ref<...> argument because
Eigen::Ref<...> satisfies the "is_eigen_dense" requirement, but can't
compile if actually used: Eigen::Ref<...> itself is not default
constructible, and so the argument std::tuple containing an
Eigen::Ref<...> isn't constructible, which results in compilation
failure.
This commit adds support for Eigen::Ref<...> by giving it its own
type_caster implementation which consists of an internal type_caster of
the referenced type, load/cast methods that dispatch to the internal
type_caster, and a unique_ptr to an Eigen::Ref<> instance that gets
set during load().
There is, of course, no performance advantage for pybind11-using code of
using Eigen::Ref<...>--we are allocating a matrix of the derived type
when loading it--but this has the advantage of allowing pybind11 to bind
transparently to C++ methods taking Eigen::Refs.
