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

Making `cppfunction` explicit broke `def_property` and friends.
The added tests would not compile without an implicit `cppfunction`.

Without the previous commit, this test generates a core dump.

With this there is no more need for manual user declarations like
`PYBIND11_DECLARE_HOLDER_TYPE(T, std::shared_ptr<T>)`. Existing ones
will still compile without error -- they will just be ignored silently.

Resolves #446.

`PyType_Ready` would usually perform the inheritance for us, but it
can't adjust `tp_basicsize` appropriately.

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 actually works with no changes, I just wasn't 100% convinced and
  decided to write a test to see if it's true.

`auto var = l[0]` has a strange quirk: `var` is actually an accessor and
not an object, so any later assignment of `var = ...` would modify l[0]
instead of `var`. This is surprising compared to the non-auto assignment
`py::object var = l[0]; var = ...`.

By overloading `operator=` on lvalue/rvalue, the expected behavior is
restored even for `auto` variables.

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.

The custom exception handling added in PR #273 is robust, but is overly
complex for declaring the most common simple C++ -> Python exception
mapping that needs only to copy `what()`.  This add a simpler
`py::register_exception<CppExp>(module, "PyExp");` function that greatly
simplifies the common basic case of translation of a simple CppException
into a simple PythonException, while not removing the more advanced
capabilities of defining custom exception handlers.

Allowed durations and non system clocks to be set from floats.

Add unit tests and documentation for the chrono cast.

The current inheritance testing isn't sufficient to detect a cache
failure; the test added here breaks PR #390, which caches the
run-time-determined return type the first time a function is called,
then reuses that cached type even though the run-time type could be
different for a future call.

This adds a static local variable (in dead code unless actually needed)
in the overload code that is used for storage if the overload is for
some convert-by-value type (such as numeric values or std::string).

This has limitations (as written up in the advanced doc), but is better
than simply not being able to overload reference or pointer methods.

Minor change that makes this example more compliant with the C++ Core
Guidelines.

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.

This commit adds support for forcing alias type initialization by
defining constructors with `py::init_alias<arg1, arg2>()` instead of
`py::init<arg1, arg2>()`.  Currently py::init<> only results in Alias
initialization if the type is extended in python, or the given
arguments can't be used to construct the base type, but can be used to
construct the alias.  py::init_alias<>, in contrast, always invokes the
constructor of the alias type.

It looks like this was already the intention of
`py::detail::init_alias`, which was forward-declared in
86d825f3, but was apparently never
finished: despite the existance of a .def method accepting it, the
`detail::init_alias` class isn't actually defined anywhere.

This commit completes the feature (or possibly repurposes it), allowing
declaration of classes that will always initialize the trampoline which
is (as I argued in #397) sometimes useful.

Type alias for alias classes with members didn't work properly: space
was only allocated for sizeof(type), but if we want to be able to put a
type_alias instance there, we need sizeof(type_alias), but
sizeof(type_alias) > sizeof(type) whenever type_alias has members.