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