Merge pull request #549 from YosysHQ/update

Update pybind11 version and fix for future python versions

1 files changed, 0 insertions, 93 deletions

diff --git a/3rdparty/pybind11/docs/intro.rst b/3rdparty/pybind11/docs/intro.rst
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index 10e1799a..00000000
--- a/3rdparty/pybind11/docs/intro.rst
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-.. image:: pybind11-logo.png
-
-About this project
-==================
-**pybind11** is a lightweight header-only library that exposes C++ types in Python
-and vice versa, mainly to create Python bindings of existing C++ code. Its
-goals and syntax are similar to the excellent `Boost.Python`_ library by David
-Abrahams: to minimize boilerplate code in traditional extension modules by
-inferring type information using compile-time introspection.
-
-.. _Boost.Python: http://www.boost.org/doc/libs/release/libs/python/doc/index.html
-
-The main issue with Boost.Python—and the reason for creating such a similar
-project—is Boost. Boost is an enormously large and complex suite of utility
-libraries that works with almost every C++ compiler in existence. This
-compatibility has its cost: arcane template tricks and workarounds are
-necessary to support the oldest and buggiest of compiler specimens. Now that
-C++11-compatible compilers are widely available, this heavy machinery has
-become an excessively large and unnecessary dependency.
-Think of this library as a tiny self-contained version of Boost.Python with
-everything stripped away that isn't relevant for binding generation. Without
-comments, the core header files only require ~4K lines of code and depend on
-Python (2.7 or 3.x, or PyPy2.7 >= 5.7) and the C++ standard library. This
-compact implementation was possible thanks to some of the new C++11 language
-features (specifically: tuples, lambda functions and variadic templates). Since
-its creation, this library has grown beyond Boost.Python in many ways, leading
-to dramatically simpler binding code in many common situations.
-
-Core features
-*************
-The following core C++ features can be mapped to Python
-
-- Functions accepting and returning custom data structures per value, reference, or pointer
-- Instance methods and static methods
-- Overloaded functions
-- Instance attributes and static attributes
-- Arbitrary exception types
-- Enumerations
-- Callbacks
-- Iterators and ranges
-- Custom operators
-- Single and multiple inheritance
-- STL data structures
-- Smart pointers with reference counting like ``std::shared_ptr``
-- Internal references with correct reference counting
-- C++ classes with virtual (and pure virtual) methods can be extended in Python
-
-Goodies
-*******
-In addition to the core functionality, pybind11 provides some extra goodies:
-
-- Python 2.7, 3.x, and PyPy (PyPy2.7 >= 5.7) are supported with an
-  implementation-agnostic interface.
-
-- It is possible to bind C++11 lambda functions with captured variables. The
-  lambda capture data is stored inside the resulting Python function object.
-
-- pybind11 uses C++11 move constructors and move assignment operators whenever
-  possible to efficiently transfer custom data types.
-
-- It's easy to expose the internal storage of custom data types through
-  Pythons' buffer protocols. This is handy e.g. for fast conversion between
-  C++ matrix classes like Eigen and NumPy without expensive copy operations.
-
-- pybind11 can automatically vectorize functions so that they are transparently
-  applied to all entries of one or more NumPy array arguments.
-
-- Python's slice-based access and assignment operations can be supported with
-  just a few lines of code.
-
-- Everything is contained in just a few header files; there is no need to link
-  against any additional libraries.
-
-- Binaries are generally smaller by a factor of at least 2 compared to
-  equivalent bindings generated by Boost.Python. A recent pybind11 conversion
-  of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary
-  size reduction of **5.4x** and compile time reduction by **5.8x**.
-
-- Function signatures are precomputed at compile time (using ``constexpr``),
-  leading to smaller binaries.
-
-- With little extra effort, C++ types can be pickled and unpickled similar to
-  regular Python objects.
-
-.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
-
-Supported compilers
-*******************
-
-1. Clang/LLVM (any non-ancient version with C++11 support)
-2. GCC 4.8 or newer
-3. Microsoft Visual Studio 2015 or newer
-4. Intel C++ compiler v17 or newer (v16 with pybind11 v2.0 and v15 with pybind11 v2.0 and a `workaround <https://github.com/pybind/pybind11/issues/276>`_ )