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71 lines
3.4 KiB
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71 lines
3.4 KiB
Markdown
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# pybind11 — Seamless operability between C++11 and Python
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[](https://travis-ci.org/wjakob/pybind11)
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[](http://pybind11.readthedocs.org/en/latest/?badge=latest)
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**pybind11** is a lightweight header 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
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[Boost.Python](http://www.boost.org/doc/libs/1_58_0/libs/python/doc/) library
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by David Abrahams: to minimize boilerplate code in traditional extension
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modules by inferring type information using compile-time introspection.
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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. The whole
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codebase requires less than 3000 lines of code and only depends on Python (2.7
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or 3.x) and the C++ standard library. This compact implementation was possible
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thanks to some of the new C++11 language features (tuples, lambda functions and
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variadic templates). Since its creation, this library has grown beyond
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Boost.Python in many ways, leading to dramatically simpler binding code in many
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common situations.
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Tutorial and reference documentation is provided at
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[http://pybind11.readthedocs.org/en/latest](http://pybind11.readthedocs.org/en/latest).
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## Core features
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pybind11 can map the following core C++ features to Python
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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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- Exceptions
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- Enumerations
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- Callbacks
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- Custom operators
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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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## Goodies
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In addition to the core functionality, pybind11 provides some extra goodies:
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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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- 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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- 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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- 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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- 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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