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Fixes #667

The sphinx version is pinned by readthedocs, but sphinx 1.3.5 is not
available with conda python 3.6. The workaround is to pin the python
version to 3.5 (it doesn't really matter for the docs build).

* Propagate unicode conversion failure

If returning a std::string with invalid utf-8 data, we currently fail
with an uninformative TypeError instead of propagating the
UnicodeDecodeError that Python sets on failure.

* Add support for u16/u32strings and literals

This adds support for wchar{16,32}_t character literals and the
associated std::u{16,32}string types.  It also folds the
character/string conversion into a single type_caster template, since
the type casters for string and wstring were mostly the same anyway.

* Added too-long and too-big character conversion errors

With this commit, when casting to a single character, as opposed to a
C-style string, we make sure the input wasn't a multi-character string
or a single character with codepoint too large for the character type.

This also changes the character cast op to CharT instead of CharT& (we
need to be able to return a temporary decoded char value, but also
because there's little gained by bothering with an lvalue return here).

Finally it changes the char caster to 'has-a-string-caster' instead of
'is-a-string-caster' because, with the cast_op change above, there's
nothing at all gained from inheritance.  This also lets us remove the
`success` from the string caster (which was only there for the char
caster) into the char caster itself.  (I also renamed it to 'none' and
inverted its value to better reflect its purpose).  The None -> nullptr
loading also now takes place only under a `convert = true` load pass.
Although it's unlikely that a function taking a char also has overloads
that can take a None, it seems marginally more correct to treat it as a
conversion.

This commit simplifies the size assumptions about character sizes with
static_asserts to back them up.

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.

* Add documentation for strings and Unicode issues

* More Unicode documentation on character literals and wide characters

* Minor doc syntax fix

The numpy documentation had a bad :file: reference (was using double
backticks instead of single backticks).

* Changed long-outdated "example" -> "tests" wording

The ConstructorStats internal docs still had "from example import", and
the main testing cpp file still used "example" in the module
description.

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

* Some clarifications to section on virtual fns

Primarily, I made it clear that PYBIND11_OVERLOAD_PURE_NAME is not "useful" but required in renaming situations. Also clarified that one should not bind to the trampoline helper class which I found tempting since it seems more explicit.

* Remove :emphasize-lines: from cpp block, seems to suppress formatting

* docs: emphasize default policy, clarify keep_alive

Emphasize the default return value policy since this statement is hidden in a wall of text. 

Add a hint that call policies are probably required for container objects.

* [Doc] Fix several errors of examples from the doc

* Add missing operator def.

* Added missing `()`

* Add missing `namespace`.

Makes room for an eventual pybind11::embedded target.

See the documentation for a description of the options.

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.

* always_construct_holder feature to support intrusively reference-counted types

* added testcase

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).

Following commit 90d278, the object code generated by the python
bindings of nanogui (github.com/wjakob/nanogui) went up by a whopping
12%. It turns out that that project has quite a few enums where we don't
really care about arithmetic operators.

This commit thus partially reverts the effects of #503 by introducing
an additional attribute py::arithmetic() that must be specified if the
arithmetic operators are desired.

* 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.