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![pybind11 logo](https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png)
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# pybind11 — Seamless operability between C++11 and Python
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[![Documentation Status](https://readthedocs.org/projects/pybind11/badge/?version=latest)](http://pybind11.readthedocs.org/en/latest/?badge=latest)
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[![Build Status](https://travis-ci.org/pybind/pybind11.svg?branch=master)](https://travis-ci.org/pybind/pybind11)
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[![Build status](https://ci.appveyor.com/api/projects/status/riaj54pn4h08xy40?svg=true)](https://ci.appveyor.com/project/wjakob/pybind11)
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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
goals and syntax are similar to the excellent
[Boost.Python](http://www.boost.org/doc/libs/1_58_0/libs/python/doc/) library
by David Abrahams: to minimize boilerplate code in traditional extension
modules by inferring type information using compile-time introspection.

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
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everything stripped away that isn't relevant for binding generation. Without
comments, the core header files only require ~2.5K lines of code and depend on
Python (2.7 or 3.x) 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.
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Tutorial and reference documentation is provided at
[http://pybind11.readthedocs.org/en/latest](http://pybind11.readthedocs.org/en/latest).
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A PDF version of the manual is available
[here](https://media.readthedocs.org/pdf/pybind11/latest/pybind11.pdf).
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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
- Instance methods and static methods
- Overloaded functions
- Instance attributes and static attributes
- Exceptions
- Enumerations
- Callbacks
- Custom operators
- STL data structures
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- Iterators and ranges
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- Smart pointers with reference counting like `std::shared_ptr`
- 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
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
  possible to efficiently transfer custom data types.

- It is possible to bind C++11 lambda functions with captured variables. The
  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
  Pythons' buffer protocols. This is handy e.g. for fast conversion between
  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
  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
  just a few lines of code.

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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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- Binaries are generally smaller by a factor of 2 or more compared to
  equivalent bindings generated by Boost.Python.

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- When supported by the compiler, two new C++14 features (relaxed constexpr and
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  return value deduction) are used to precompute function signatures at compile
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  time, leading to smaller binaries.

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- With little extra effort, C++ types can be pickled and unpickled similar to
  regular Python objects.

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## Supported compilers

1. Clang/LLVM (any non-ancient version with C++11 support)
2. GCC (any non-ancient version with C++11 support)
3. Microsoft Visual Studio 2015 or newer
4. Intel C++ compiler v15 or newer
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5. Cygwin
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## About

This project was created by [Wenzel Jakob](https://www.mitsuba-renderer.org/~wenzel/).
Significant features and/or improvements to the code were contributed by
Jonas Adler,
Sylvain Corlay,
Axel Huebl,
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@hulucc,
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Sergey Lyskov
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Johan Mabille,
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Tomasz Miąsko,
Dean Moldovan,
Ben Pritchard, and
Boris Schäling.
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### License

pybind11 is provided under a BSD-style license that can be found in the
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``LICENSE`` file. By using, distributing, or contributing to this project,
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you agree to the terms and conditions of this license.