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numpy arrays aren't currently properly setting base: by setting `->base`
directly, the base doesn't follow what numpy expects and documents (that
is, following chained array bases to the root array).

This fixes the behaviour by using numpy's PyArray_SetBaseObject to set
the base instead, and then updates the tests to reflect the fixed
behaviour.

A few of pybind's numpy constants are using the numpy-deprecated names
(without "ARRAY_" in them); updated our names to be consistent with
current numpy code.

noexcept deduction, added in PR #555, doesn't work with clang's
-std=c++1z; and while it works with g++, it isn't entirely clear to me
that it is required to work in C++17.

What should work, however, is that C++17 allows implicit conversion of a
`noexcept(true)` function pointer to a `noexcept(false)` (i.e.  default,
noexcept-not-specified) function pointer.  That was breaking in pybind11
because the cpp_function template used for lambdas provided a better
match (i.e. without requiring an implicit conversion), but it then
failed.

This commit takes a different approach of using SFINAE on the lambda
function to prevent it from matching a non-lambda object, which then
gets implicit conversion from a `noexcept` function pointer to a
`noexcept(false)` function pointer.  This much nicer solution also gets
rid of the C++17 NOEXCEPT macros, and works in both clang and g++.

This reverts commit bee8827a.

* 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.

(Identifiers starting with underscores are reserved by the standard)
Also fixed a typo in a comment.

* 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.

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.

Newer standard libraries use compiler intrinsics for std::index_sequence
which makes it ‘free’. This prevents hitting instantiation limits for
recursive templates (-ftemplate-depth).

Previously all types are marked unaligned in buffer format strings,
now we test for alignment before adding the '=' marker.

* `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.

* Deprecate the `py::object::str()` member function since `py::str(obj)`
  is now equivalent and preferred

* Make `py::repr()` a free function

* Make sure obj.cast<T>() works as expected when T is a Python type

`obj.cast<T>()` should be the same as `T(obj)`, i.e. it should convert
the given object to a different Python type. However, `obj.cast<T>()`
usually calls `type_caster::load()` which only checks the type without
doing any actual conversion. That causes a very unexpected `cast_error`.
This commit makes it so that `obj.cast<T>()` and `T(obj)` are the same
when T is a Python type.

* Simplify pytypes converting constructor implementation

It's not necessary to maintain a full set of converting constructors
and assignment operators + const& and &&. A single converting const&
constructor will work and there is no impact on binary size. On the
other hand, the conversion functions can be significantly simplified.

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
});
```

* Also added unsafe version without checks

(avoid code bloat if possible)

NumPy internals are stored under "_numpy_internals" key.

PYBIND11_NUMPY_DTYPE_EX(Type, F1, "N1", F2, "N2", ...)

This avoid a hashmap lookup since the pointer to the list of
direct converters is now cached in the typeinfo.

We have various classes that have non-explicit constructors that accept
a single argument, which is implicitly making them implicitly
convertible from the argument.  In a few cases, this is desirable (e.g.
implicit conversion of std::string to py::str, or conversion of double
to py::float_); in many others, however, it is unintended (e.g. implicit
conversion of size_t to some pre-declared py::array_t<T> type).

This disables most of the unwanted implicit conversions by marking them
`explicit`, and comments the ones that are deliberately left implicit.

This convenience function ensures that a py::object is either a
py::array, or the implementation will try to convert it into one. Layout
requirements (such as c_style or f_style) can be also be provided.

This patch adds an extra base handle parameter to most ``py::array`` and
``py::array_t<>`` constructors. If specified along with a pointer to
data, the base object will be registered within NumPy, which increases
the base's reference count. This feature is useful to create shallow
copies of C++ or Python arrays while ensuring that the owners of the
underlying can't be garbage collected while referenced by NumPy.

The commit also adds a simple test function involving a ``wrap()``
function that creates shallow copies of various N-D arrays.

This also adds the `hasattr` and `getattr` functions which are needed
with the new attribute behavior. The new functions behave exactly like
their Python counterparts.

Similarly `object` gets a `contains` method which calls `__contains__`,
i.e. it's the same as the `in` keyword in Python.