* Avoid C-style const casts
Replace C-style casts that discard `const` with `const_cast` (and, where
necessary, `reinterpret_cast` as well).
* Warn about C-style const-discarding casts
Change pybind11_enable_warnings to also enable `-Wcast-qual` (warn if a
C-style cast discards `const`) by default. The previous commit should
have gotten rid of all of these (at least, all the ones that tripped in
my build, which included the tests), and this should discourage more
from newly appearing.
Fixes#656.
Before this commit, the problematic sequence was:
1. `catch (const std::exception &e)` gets a Python exception,
i.e. `error_already_set`.
2. `PyErr_SetString(PyExc_ImportError, e.what())` sets an `ImportError`.
3. `~error_already_set()` now runs, but `gil_scoped_acquire` fails due
to an unhandled `ImportError` (which was just set in step 2).
This commit adds a separate catch block for Python exceptions which just
clears the Python error state a little earlier and replaces it with an
`ImportError`, thus making sure that there is only a single Python
exception in flight at a time. (After step 2 in the sequence above,
there were effectively two Python expections set.)
* Fix debugging output for nameless py::arg annotations
This fixes a couple bugs with nameless py::arg() (introduced in #634)
annotations:
- the argument name was being used in debug mode without checking that
it exists (which would result in the std::string construction throwing
an exception for being invoked with a nullptr)
- the error output says "keyword arguments", but py::arg_v() can now
also be used for positional argument defaults.
- the debugging output "in function named 'blah'" was overly verbose:
changed it to just "in function 'blah'".
* Fix missing space in debug test string
* Moved tests from issues to methods_and_attributes
This changes the function dispatching code for overloaded functions into
a two-pass procedure where we first try all overloads with
`convert=false` for all arguments. If no function calls succeeds in the
first pass, we then try a second pass where we allow arguments to have
`convert=true` (unless, of course, the argument was explicitly specified
with `py::arg().noconvert()`).
For non-overloaded methods, the two-pass procedure is skipped (we just
make the overload-allowed call). The second pass is also skipped if it
would result in the same thing (i.e. where all arguments are
`.noconvert()` arguments).
This adds support for controlling the `convert` flag of arguments
through the py::arg annotation. This then allows arguments to be
flagged as non-converting, which the type_caster is able to use to
request different behaviour.
Currently, AFAICS `convert` is only used for type converters of regular
pybind11-registered types; all of the other core type_casters ignore it.
We can, however, repurpose it to control internal conversion of
converters like Eigen and `array`: most usefully to give callers a way
to disable the conversion that would otherwise occur when a
`Eigen::Ref<const Eigen::Matrix>` argument is passed a numpy array that
requires conversion (either because it has an incompatible stride or the
wrong dtype).
Specifying a noconvert looks like one of these:
m.def("f1", &f, "a"_a.noconvert() = "default"); // Named, default, noconvert
m.def("f2", &f, "a"_a.noconvert()); // Named, no default, no converting
m.def("f3", &f, py::arg().noconvert()); // Unnamed, no default, no converting
(The last part--being able to declare a py::arg without a name--is new:
previous py::arg() only accepted named keyword arguments).
Such an non-convert argument is then passed `convert = false` by the
type caster when loading the argument. Whether this has an effect is up
to the type caster itself, but as mentioned above, this would be
extremely helpful for the Eigen support to give a nicer way to specify
a "no-copy" mode than the custom wrapper in the current PR, and
moreover isn't an Eigen-specific hack.
Arithmetic and complex casters now only do a converting cast when
`convert=true`; previously they would convert always (e.g. when passing
an int to a float-accepting function, or a float to complex-accepting
function).
This cleans up the previous commit slightly by further reducing the
function call arguments to a single struct (containing the
function_record, arguments vector, and parent).
Although this doesn't currently change anything, it does allow for
future functionality to have a place for precalls to store temporary
objects that need to be destroyed after a function call (whether or not
the call succeeds).
As a concrete example, with this change #625 could be easily implemented
(I think) by adding a std::unique_ptr<gil_scoped_release> member to the
`function_call` struct with a precall that actually constructs it.
Without this, the precall can't do that: the postcall won't be invoked
if the call throws an exception.
This doesn't seems to affect the .so size noticeably (either way).
This commit rewrites the function dispatcher code to support mixing
regular arguments with py::args/py::kwargs arguments. It also
simplifies the argument loader noticeably as it no longer has to worry
about args/kwargs: all of that is now sorted out in the dispatcher,
which now simply appends a tuple/dict if the function takes
py::args/py::kwargs, then passes all the arguments in a vector.
When the argument loader hit a py::args or py::kwargs, it doesn't do
anything special: it just calls the appropriate type_caster just like it
does for any other argument (thus removing the previous special cases
for args/kwargs).
Switching to passing arguments in a single std::vector instead of a pair
of tuples also makes things simpler, both in the dispatch and the
argument_loader: since this argument list is strictly pybind-internal
(i.e. it never goes to Python) we have no particular reason to use a
Python tuple here.
Some (intentional) restrictions:
- you may not bind a function that has args/kwargs somewhere other than
the end (this somewhat matches Python, and keeps the dispatch code a
little cleaner by being able to not worry about where to inject the
args/kwargs in the argument list).
- If you specify an argument both positionally and via a keyword
argument, you get a TypeError alerting you to this (as you do in
Python).
* Abstract away some holder functionality (resolve#585)
Custom holder types which don't have `.get()` can select the correct
function to call by specializing `holder_traits`.
* Add support for move-only holders (fix#605)
* Clarify PYBIND11_NUMPY_DTYPE documentation
The current documentation and example reads as though
PYBIND11_NUMPY_DTYPE is a declarative macro along the same lines as
PYBIND11_DECLARE_HOLDER_TYPE, but it isn't. The changes the
documentation and docs example to make it clear that you need to "call"
the macro.
* Add satisfies_{all,any,none}_of<T, Preds>
`satisfies_all_of<T, Pred1, Pred2, Pred3>` is a nice legibility-enhanced
shortcut for `is_all<Pred1<T>, Pred2<T>, Pred3<T>>`.
* Give better error message for non-POD dtype attempts
If you try to use a non-POD data type, you get difficult-to-interpret
compilation errors (about ::name() not being a member of an internal
pybind11 struct, among others), for which isn't at all obvious what the
problem is.
This adds a static_assert for such cases.
It also changes the base case from an empty struct to the is_pod_struct
case by no longer using `enable_if<is_pod_struct>` but instead using a
static_assert: thus specializations avoid the base class, POD types
work, and non-POD types (and unimplemented POD types like std::array)
get a more informative static_assert failure.
* Prefix macros with PYBIND11_
numpy.h uses unprefixed macros, which seems undesirable. This prefixes
them with PYBIND11_ to match all the other macros in numpy.h (and
elsewhere).
* Add long double support
This adds long double and std::complex<long double> support for numpy
arrays.
This allows some simplification of the code used to generate format
descriptors; the new code uses fewer macros, instead putting the code as
different templated options; the template conditions end up simpler with
this because we are now supporting all basic C++ arithmetic types (and
so can use is_arithmetic instead of is_integral + multiple
different specializations).
In addition to testing that it is indeed working in the test script, it
also adds various offset and size calculations there, which
fixes the test failures under x86 compilations.
* Make 'any' the default markup role for Sphinx docs
* Automate generation of reference docs with doxygen and breathe
* Improve reference docs coverage
* Fixed a regression that was introduced in the PyPy patch: use ht_qualname_meta instead of ht_qualname to fix PyHeapTypeObject->ht_qualname field.
* Added a qualname/repr test that works in both Python 3.3+ and previous versions
This commit includes modifications that are needed to get pybind11 to work with PyPy. The full test suite compiles and runs except for a last few functions that are commented out (due to problems in PyPy that were reported on the PyPy bugtracker).
Two somewhat intrusive changes were needed to make it possible: two new tags ``py::buffer_protocol()`` and ``py::metaclass()`` must now be specified to the ``class_`` constructor if the class uses the buffer protocol and/or requires a metaclass (e.g. for static properties).
Note that this is only for the PyPy version based on Python 2.7 for now. When the PyPy 3.x has caught up in terms of cpyext compliance, a PyPy 3.x patch will follow.
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.
When compiling in C++17 mode the noexcept specifier is part of the
function type. This causes a failure in pybind11 because, by omitting
a noexcept specifier when deducing function return and argument types,
we are implicitly making `noexcept(false)` part of the type.
This means that functions with `noexcept` fail to match the function
templates in cpp_function (and other places), and we get compilation
failure (we end up trying to fit it into the lambda function version,
which fails since a function pointer has no `operator()`).
We can, however, deduce the true/false `B` in noexcept(B), so we don't
need to add a whole other set of overloads, but need to deduce the extra
argument when under C++17. That will *not* work under pre-C++17,
however.
This commit adds two macros to fix the problem: under C++17 (with the
appropriate feature macro set) they provide an extra `bool NoExceptions`
template argument and provide the `noexcept(NoExceptions)` deduced
specifier. Under pre-C++17 they expand to nothing.
This is needed to compile pybind11 with gcc7 under -std=c++17.
Since the argument loader split off from the tuple converter, it is
never called with a `convert` argument set to anything but true. This
removes the argument entirely, passing a literal `true` from within
`argument_loader` to the individual value casters.
This adds automatic casting when assigning to python types like dict,
list, and attributes. Instead of:
dict["key"] = py::cast(val);
m.attr("foo") = py::cast(true);
list.append(py::cast(42));
you can now simply write:
dict["key"] = val;
m.attr("foo") = true;
list.append(42);
Casts needing extra parameters (e.g. for a non-default rvp) still
require the py::cast() call. set::add() is also supported.
All usage is channeled through a SFINAE implementation which either just returns or casts.
Combined non-converting handle and autocasting template methods via a
helper method that either just returns (handle) or casts (C++ type).
* Added ternary support with descr args
Current the `_<bool>(a, b)` ternary support only works for `char[]` `a`
and `b`; this commit allows it to work for `descr` `a` and `b` arguments
as well.
* Add support for std::valarray to stl.h
This abstracts the std::array into a `array_caster` which can then be
used with either std::array or std::valarray, the main difference being
that std::valarray is resizable. (It also lets the array_caster be
potentially used for other std::array-like interfaces, much as the
list_caster and map_caster currently provide).
* Small stl.h cleanups
- Remove redundant `type` typedefs
- make internal list_caster methods private
Newer standard libraries use compiler intrinsics for std::index_sequence
which makes it ‘free’. This prevents hitting instantiation limits for
recursive templates (-ftemplate-depth).
This is needed in order to allow the tuple caster to accept any sequence
while keeping the argument loader fast. There is also very little overlap
between the two classes which makes the separation clean. It’s also good
practice not to have completely new functionality in a specialization.
Using a complicated declval here was pointlessly complicated: we
already know the type, because that's what cast_op_type<T> is in the
first place. (The declval also broke MSVC).
This adds a `detail::cast_op<T>(caster)` function which handles the
rather verbose:
caster.operator typename CasterType::template cast_op_type<T>()
which allows various places to use the shorter and clearer:
cast_op<T>(caster)
instead of the full verbose cast operator invocation.
stl casters were using a value cast to (Value) or (Key), but that isn't
always appropriate. This changes it to use the appropriate value
converter's cast_op_type.
C++ exceptions are destructed in the context of the code that catches
them. At this point, the Python GIL may not be held, which could lead
to crashes with the previous implementation.
PyErr_Fetch and PyErr_Restore should always occur in pairs, which was
not the case for the previous implementation. To clear the exception,
the new approach uses PyErr_Restore && PyErr_Clear instead of simply
decreasing the reference counts of the exception objects.
