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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>`_ )